scholarly journals Antenna Miniaturization with MEMS Tunable Capacitors: Techniques and Trade-Offs

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Samantha Caporal Del Barrio ◽  
Art Morris ◽  
Gert F. Pedersen
Keyword(s):  
Mobile Device ◽  
Insertion Loss ◽  
State Of The Art ◽  
Tunable Capacitors ◽  
Antenna Miniaturization ◽  
Trade Offs ◽  
Operating Bandwidth ◽  
Tunable Antennas ◽  
The Impact

In today’s mobile device market, there is a strong need for efficient antenna miniaturization. Tunable antennas are a very promising way to reduce antenna volume while enlarging its operating bandwidth. MEMS tunable capacitors are state-of-the-art in terms of insertion loss. Their characteristics are used in this investigation. This paper uses field simulations to highlight the trade-offs between the design of the tuner and the design of the antenna, especially the impact of the location of the tuner and the degree of miniaturization. Codesigning the tuner and the antenna is essential to optimize radiated performance.

scholarly journals Carbon Dynamics in the Northeastern Qinghai–Tibetan Plateau from 1990 to 2030 Using Landsat Land Use/Cover Change Data

2020 ◽  
Vol 12 (3) ◽  
pp. 528 ◽  
Author(s):  
Jingye Li ◽  
Jian Gong ◽  
Jean-Michel Guldmann ◽  
Shicheng Li ◽  
Jie Zhu
Keyword(s):  
Land Use ◽  
Tibetan Plateau ◽  
Carbon Storage ◽  
Sharp Decrease ◽  
Total Carbon ◽  
Qinghai Lake ◽  
Lake Basin ◽  
Ecosystem Carbon ◽  
Trade Offs ◽  
The Impact

Land use/cover change (LUCC) has an important impact on the terrestrial carbon cycle. The spatial distribution of regional carbon reserves can provide the scientific basis for the management of ecosystem carbon storage and the formulation of ecological and environmental policies. This paper proposes a method combining the CA-based FLUS model and the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model to assess the temporal and spatial changes in ecosystem carbon storage due to land-use changes over 1990–2015 in the Qinghai Lake Basin (QLB). Furthermore, future ecosystem carbon storage is simulated and evaluated over 2020–2030 under three scenarios of natural growth (NG), cropland protection (CP), and ecological protection (EP). The long-term spatial variations in carbon storage in the QLB are discussed. The results show that: (1) Carbon storage in the QLB decreased at first (1990–2000) and increased later (2000–2010), with total carbon storage increasing by 1.60 Tg C (Teragram: a unit of mass equal to 1012 g). From 2010 to 2015, carbon storage displayed a downward trend, with a sharp decrease in wetlands and croplands as the main cause; (2) Under the NG scenario, carbon reserves decrease by 0.69 Tg C over 2020–2030. These reserves increase significantly by 6.77 Tg C and 7.54 Tg C under the CP and EP scenarios, respectively, thus promoting the benign development of the regional ecological environment. This study improves our understanding on the impact of land-use change on carbon storage for the QLB in the northeastern Qinghai–Tibetan Plateau (QTP).

scholarly journals Comparison of Industrial Quenching Oils

Metals ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 250
Author(s):  
Jiří Hájek ◽  
Zaneta Dlouha ◽  
Vojtěch Průcha
Keyword(s):  
State Of The Art ◽  
Cooling Capacity ◽  
Steel Grade ◽  
Cooling Curves ◽  
Cooling Process ◽  
Industrial Practice ◽  
Product Size ◽  
Cct Curve ◽  
Hardening Power ◽  
The Impact

This article is a response to the state of the art in monitoring the cooling capacity of quenching oils in industrial practice. Very often, a hardening shop requires a report with data on the cooling process for a particular quenching oil. However, the interpretation of the data can be rather difficult. The main goal of our work was to compare various criteria used for evaluating quenching oils. Those of which prove essential for operation in tempering plants would then be introduced into practice. Furthermore, the article describes monitoring the changes in the properties of a quenching oil used in a hardening shop, the effects of quenching oil temperature on its cooling capacity and the impact of the water content on certain cooling parameters of selected oils. Cooling curves were measured (including cooling rates and the time to reach relevant temperatures) according to ISO 9950. The hardening power of the oil and the area below the cooling rate curve as a function of temperature (amount of heat removed in the nose region of the Continuous cooling transformation - CCT curve) were calculated. V-values based on the work of Tamura, reflecting the steel type and its CCT curve, were calculated as well. All the data were compared against the hardness and microstructure on a section through a cylinder made of EN C35 steel cooled in the particular oil. Based on the results, criteria are recommended for assessing the suitability of a quenching oil for a specific steel grade and product size. The quenching oils used in the experiment were Houghto Quench C120, Paramo TK 22, Paramo TK 46, CS Noro MO 46 and Durixol W72.

scholarly journals Smoothing additive manufactured parts using ns-pulsed laser radiation

2021 ◽  
Author(s):  
Florian Kuisat ◽  
Fernando Lasagni ◽  
Andrés Fabián Lasagni
Keyword(s):  
Surface Roughness ◽  
Mechanical Performance ◽  
State Of The Art ◽  
Pulsed Laser ◽  
Industrial Applications ◽  
Laser Source ◽  
Pulsed Laser Radiation ◽  
Current State ◽  
The Impact

AbstractIt is well known that the surface topography of a part can affect its mechanical performance, which is typical in additive manufacturing. In this context, we report about the surface modification of additive manufactured components made of Titanium 64 (Ti64) and Scalmalloy®, using a pulsed laser, with the aim of reducing their surface roughness. In our experiments, a nanosecond-pulsed infrared laser source with variable pulse durations between 8 and 200 ns was applied. The impact of varying a large number of parameters on the surface quality of the smoothed areas was investigated. The results demonstrated a reduction of surface roughness Sa by more than 80% for Titanium 64 and by 65% for Scalmalloy® samples. This allows to extend the applicability of additive manufactured components beyond the current state of the art and break new ground for the application in various industrial applications such as in aerospace.

scholarly journals Discrete choice experiment for eliciting preference for health services for patients with ALS and their informal caregivers

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Katy Tobin ◽  
Sinead Maguire ◽  
Bernie Corr ◽  
Charles Normand ◽  
Orla Hardiman ◽  
...  
Keyword(s):  
Health Services ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Strong Preference ◽  
Multidisciplinary Teams ◽  
Relative Importance ◽  
Trade Offs ◽  
Als Patients ◽  
The Impact

Abstract Background Amyotrophic Lateral Sclerosis (ALS) is a progressive neurodegenerative condition with a mean life expectancy of 3 years from first symptom. Understanding the factors that are important to both patients and their caregivers has the potential to enhance service delivery and engagement, and improve efficiency. The Discrete Choice Experiment (DCE) is a stated preferences method which asks service users to make trade-offs for various attributes of health services. This method is used to quantify preferences and shows the relative importance of the attributes in the experiment, to the service user. Methods A DCE with nine choice sets was developed to measure the preferences for health services of ALS patients and their caregivers and the relative importance of various aspects of care, such as timing of care, availability of services, and decision making. The DCE was presented to patients with ALS, and their caregivers, recruited from a national multidisciplinary clinic. A random effects probit model was applied to estimate the impact of each attribute on a participant’s choice. Results Patients demonstrated the strongest preferences about timing of receiving information about ALS. A strong preference was also placed on seeing the hospice care team later rather than early on in the illness. Patients also indicated their willingness to consider the use of communication devices. Grouping by stage of disease, patients who were in earlier stages of disease showed a strong preference for receipt of extensive information about ALS at the time of diagnosis. Caregivers showed a strong preference for engagement with healthcare professionals, an attribute that was not prioritised by patients. Conclusions The DCE method can be useful in uncovering priorities of patients and caregivers with ALS. Patients and caregivers have different priorities relating to health services and the provision of care in ALS, and patient preferences differ based on the stage and duration of their illness. Multidisciplinary teams must calibrate the delivery of care in the context of the differing expectations, needs and priorities of the patient/caregiver dyad.

scholarly journals Modeling Energy Communities with Collective Photovoltaic Self-Consumption: Synergies between a Small City and a Winery in Portugal

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 323
Author(s):  
Guilherme Pontes Luz ◽  
Rodrigo Amaro e Silva
Keyword(s):  
Economic Feasibility ◽  
Small City ◽  
Total System ◽  
Trade Offs ◽  
Southern Portugal ◽  
Energy Community ◽  
Individual Self ◽  
The Impact ◽  
The City ◽  
Modest Reduction

The recently approved regulation on Energy Communities in Europe is paving the way for new collective forms of energy consumption and production, mainly based on photovoltaics. However, energy modeling approaches that can adequately evaluate the impact of these new regulations on energy community configurations are still lacking, particularly with regards to the grid tariffs imposed on collective systems. Thus, the present work models three different energy community configurations sustained on collective photovoltaics self-consumption for a small city in southern Portugal. This energy community, which integrates the city consumers and a local winery, was modeled using the Python-based Calliope framework. Using real electricity demand data from power transformers and an actual winery, the techno-economic feasibility of each configuration was assessed. Results show that all collective arrangements can promote a higher penetration of photovoltaic capacity (up to 23%) and a modest reduction in the overall cost of electricity (up to 8%). However, there are clear trade-offs between the different pathways: more centralized configurations have 53% lower installation costs but are more sensitive to grid use costs (which can represent up to 74% of the total system costs). Moreover, key actor’s individual self-consumption rate may decrease by 10% in order to benefit the energy community as a whole.

scholarly journals Cash Flow Bullwhip—Literature Review and Research Perspectives

Logistics ◽  
2021 ◽  
Vol 5 (1) ◽  
pp. 8
Author(s):  
Hicham Lamzaouek ◽  
Hicham Drissi ◽  
Naima El Haoud
Keyword(s):  
Literature Review ◽  
Customer Service ◽  
Cash Flow ◽  
State Of The Art ◽  
Research Work ◽  
Bullwhip Effect ◽  
Research Perspectives ◽  
Financial Perspective ◽  
The Impact ◽  
Exhaustive List

The bullwhip effect is a pervasive phenomenon in all supply chains causing excessive inventory, delivery delays, deterioration of customer service, and high costs. Some researchers have studied this phenomenon from a financial perspective by shedding light on the phenomenon of cash flow bullwhip (CFB). The objective of this article is to provide the state of the art in relation to research work on CFB. Our ambition is not to make an exhaustive list, but to synthesize the main contributions, to enable us to identify other interesting research perspectives. In this regard, certain lines of research remain insufficiently explored, such as the role that supply chain digitization could play in controlling CFB, the impact of CFB on the profitability of companies, or the impacts of the omnichannel commerce on CFB.

scholarly journals Temperature Characterization of Liquid Crystal Dielectric Image Line Phase Shifter for Millimeter-Wave Applications

Crystals ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 63
Author(s):  
Henning Tesmer ◽  
Rani Razzouk ◽  
Ersin Polat ◽  
Dongwei Wang ◽  
Rolf Jakoby ◽  
...  
Keyword(s):  
Liquid Crystal ◽  
Millimeter Wave ◽  
Insertion Loss ◽  
Phase Shifter ◽  
Ground Plane ◽  
Temperature Dependent ◽  
Differential Phase ◽  
Dependent Behavior ◽  
The Impact ◽  
Temperature Dependent Behavior

In this paper we investigate the temperature dependent behavior of a liquid crystal (LC) loaded tunable dielectric image guide (DIG) phase shifter at millimeter-wave frequencies from 80 GHz to 110 GHz for future high data rate communications. The adhesive, necessary for precise fabrication, is analyzed before temperature dependent behavior of the component is shown, using the nematic LC-mixture GT7-29001. The temperature characterization is conducted by changing the temperature of the LC DIG’s ground plane between −10∘C and 80 ∘C. The orientation of the LC molecules, and therefore the effective macroscopic relative permittivity of the DIG, is changed by inserting the temperature setup in a fixture with rotatable magnets. Temperature independent matching can be observed, while the insertion loss gradually increases with temperature for both highest and lowest permittivity of the LC. At 80 ∘C the insertion loss is up to 1.3dB higher and at −10∘C it is 0.6dB lower than the insertion loss present at 20 ∘C. In addition, the achievable differential phase is reduced with increasing temperature. The impact of molecule alignment to this reduction is shown for the phase shifter and an estimated 85% of the anisotropy is still usable with an LC DIG phase shifter when increasing the temperature from 20 ∘C to 80 ∘C. Higher reduction of differential phase is present at higher frequencies as the electrical length of the phase shifter increases. A maximum difference in differential phase of 72∘ is present at 110 GHz, when increasing the temperature from 20 ∘C to 80 ∘C. Nevertheless, a well predictable, quasi-linear behavior can be observed at the covered temperature range, highlighting the potential of LC-based dielectric components at millimeter wave frequencies.

scholarly journals Assessing the Impact of the Loss Function, Architecture and Image Type for Deep Learning-Based Wildfire Segmentation

2021 ◽  
Vol 11 (15) ◽  
pp. 7046
Author(s):  
Jorge Francisco Ciprián-Sánchez ◽  
Gilberto Ochoa-Ruiz ◽  
Lucile Rossi ◽  
Frédéric Morandini
Keyword(s):  
Deep Learning ◽  
Loss Function ◽  
State Of The Art ◽  
Fire Detection ◽  
Loss Functions ◽  
Wildfire Spread ◽  
Combine Information ◽  
The Impact ◽  
Image Type ◽  
Segmentation Models

Wildfires stand as one of the most relevant natural disasters worldwide, particularly more so due to the effect of climate change and its impact on various societal and environmental levels. In this regard, a significant amount of research has been done in order to address this issue, deploying a wide variety of technologies and following a multi-disciplinary approach. Notably, computer vision has played a fundamental role in this regard. It can be used to extract and combine information from several imaging modalities in regard to fire detection, characterization and wildfire spread forecasting. In recent years, there has been work pertaining to Deep Learning (DL)-based fire segmentation, showing very promising results. However, it is currently unclear whether the architecture of a model, its loss function, or the image type employed (visible, infrared, or fused) has the most impact on the fire segmentation results. In the present work, we evaluate different combinations of state-of-the-art (SOTA) DL architectures, loss functions, and types of images to identify the parameters most relevant to improve the segmentation results. We benchmark them to identify the top-performing ones and compare them to traditional fire segmentation techniques. Finally, we evaluate if the addition of attention modules on the best performing architecture can further improve the segmentation results. To the best of our knowledge, this is the first work that evaluates the impact of the architecture, loss function, and image type in the performance of DL-based wildfire segmentation models.

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