Desired Period Research Articles

Bioresorbable Multilayer Organic-Inorganic Films for Bioelectronic Systems.

Bioresorbable electronic devices as temporary biomedical implants represent an emerging class of technology relevant to a range of patient conditions currently addressed with technologies that require surgical explantation after a desired period of use. Obtaining reliable performance and favorable degradation behavior demands materials that can serve as biofluid barriers in encapsulating structures that avoid premature degradation of active electronic components. Here, this work presents a materials design that addresses this need, with properties in water impermeability, mechanical flexibility, and processability that are superior to alternatives. The approach uses multilayer assemblies of alternating films of polyanhydride and silicon oxynitride formed by spin-coating and plasma-enhanced chemical vapor deposition , respectively. Experimental and theoretical studies investigate the effects of material composition and multilayer structure on water barrier performance, water distribution, and degradation behavior. Demonstrations with inductor-capacitor circuits, wireless power transfer systems, and wireless optoelectronic devices illustrate the performance of this materials system as a bioresorbable encapsulating structure.

Formulation and In-Vitro Evaluation of Amlodipine Besylate Floating Tablets Using Different Polymers

Gastric-retentive amlodipine besylate effervescent tablets have been developed using a variety of hydrophilic polymers. Formulations were developed using different grades of different concentrations of polymer. H. HPMC K4M, HPMC K15M, HPMC K100 and xanthan gum were used as polymeric substances. The formulated mixtures have been subjected to various pre-formulation studies and flow properties, and all formulations show that the powder mixtures have good flow properties. Among all formulations, drug release was delayed for the desired period, H. 12 hours, for the HPMC K100 formulation as a polymer. The dissolution data showed that formulations made with HPMC K100M and xanthan gum as the polymer sustained drug release for the desired period. H. 12 hours at a concentration of 150 mg. On the other hand, in formulations containing HPMC K4M, HPMC K15M as polymer failed to produce the desired drug release. Therefore, the floating drug delivery system of amlodipine using the appropriate amount of appropriate polymer can increase the activity of the drug by prolonging the gastric residence time or decreasing the floating lag time. Keywords: Gastric-retentive, amlodipine besylate, effervescent tablets, HPMC K4M

Microwave Angiography by Ultra-Wideband Sounding: A Preliminary Investigation.

Angiography is a very informative method for physicians such as cardiologists, neurologists and neuroscientists. The current modalities experience some shortages, e.g., ultrasound is very operator dependent. The computerized tomography (CT) and magnetic resonance (MR) angiography are very expensive and near infrared spectroscopy cannot capture the deep arteries. Microwave technology has the potential to address some of these issues while compromising between operator dependency, cost, speed, penetration depth and resolution. This paper studies the feasibility of microwave signals for monitoring of arteries. To this aim, a homogenous phantom mimicking body tissue is built. Four elastic tubes simulate arteries and a mechanical system creates pulsations in these arteries. A multiple input multiple output (MIMO) array of ultra-wideband (UWB) transmitters and receivers illuminates the phantom and captures the reflected signals over the desired observation time period. Since we are only interested in the imaging of dynamic parts, i.e., arteries, the static clutters can be suppressed easily by background subtraction method. To obtain a fast image of arteries, which are pulsating with the heartbeat rate, we calculate the Fourier transform of each channel of the MIMO system over the observation time and apply delay and sum (DAS) beamforming method on the heartbeat rate aligned spectral component. The results show that the lateral and longitudinal images and motion mode (M-mode) time series of different points of phantom have the potential to be used for diagnosis.

Tuning Wave Energy Converters to local wave conditions

A Wave Energy Converter (WEC) cannot operate efficiently if left alone floating to the mercy of the random sea surface. Moreover, high waves may impose destructive forces while contributing nil energy production in return. For a WEC to be efficient, its natural frequency should be close to the peak frequency of a wave spectrum. At the resonance or another lower natural frequency, dynamic responses are more regular, and thus, the power take-off system (PTO) can operate in a more efficient manner. This paper introduces a general systematic methodology for tuning the natural frequency of a resonant WEC for the desired degree of freedom and converting dynamic responses into power. A barge is used as a case study to tune its roll and heave natural period, which in general are much lower than the peak period of swells. The roll natural period is increased by hanging subsea structures to the sides of the vessel by means of mooring lines, see Fig. 1. The size of the structures and their entrapped water increase the roll mass moment of inertia to achieve the desired period. For the heave response, the natural period raises by adding skirts to the sides of the vessel, increasing the entrapped water. The resonant motions are significantly suppressed by means of the drag force acting on the subsea structures. Thus, the extreme drag forces acting on the structures act as a damper to the vessel response. These forces are transferred to the mooring lines, which can be converted into a rotary motion of a shaft of the PTO. Our application focuses on the Galapagos Islands, where narrow, low-frequency southerly swells with a typical 13 s peak period dominate the wave climate. This study allows for a systematic design of resonant-type WECs, which is necessary for the development of technical and economic feasibility studies of various novel and existing concepts.
 
 Figure 1: Schematic representation of resonant WEC with tuned roll natural period

Predicting Residential Photovoltaic Adoption Intention of Potential Prosumers in Thailand: A Theory of Planned Behavior Model

The current study investigates economic expectations and socio-psychological factors influencing individuals’ residential photovoltaic (RPV) adoption intentions in Thailand. The theory of planned behavior (TPB) and the diffusion of innovation theory provide a framework for our predictor selection. We obtained the data from a nationwide survey on electricity prosumer infrastructure. RPV non-users (N = 760) were asked to rate their RPV knowledge, attitudes, perceived behavioral controls (PBCs), norms, and innovativeness. They then read scenarios describing the current RPV installation cost and payback rate. They rated their adoption intention and specified their intended system capacity, affordable installation cost, and desirable payback period. The gaps between the actual and desired installation costs and the internal rate of return were calculated. These economic expectation gaps, attitudes based on financial benefits, PBC based on perceived financial barriers, social norms, and innovativeness significantly predicted the adoption intention. On the other hand, perceived knowledge, attitudes based on environmental and image benefits, and PBC based on anticipated troubles and inconveniences failed to predict intention. The implications of the TPB model for RPV adoption were discussed.

Microbeam X-ray Reanalysis on Periodically Assembled Poly(β-Hydroxybutyric acid-Co-β-hydroxyvaleric acid) Tailored with Diluents.

Self-assembly of 3D interiors and iridescence properties of poly(β-hydroxybutyric acid-co-β-hydroxyvaleric acid) (PHBV) periodic crystals are examined using microcopy techniques and microbeam X-ray diffraction. Morphology of PHBV can be tailored by crystallizing in presence of poly(vinyl acetate) (PVAc) or poly(trimethylene adipate) (PTA) for displaying desired periodicity patterns. The regular alternate-layered lamellae of banded PHBV crystal aggregates, resembling the structures the natural mineral moonstone or nacre, are examined to elaborate the origin of light interference and formation mechanisms of periodic lamellar aggregation of PHBV spherulites. By using PHBV as a convenient model and the crystal diffraction data, this continuing work demonstrates unique methodology for effectively studying the periodic assembly in widely varying polymers with similar aggregates. Grating structures in periodically assembled polymer crystals can be tailored for microstructure with orderly periodicity.

Effects of a 10-week musical instrument training on cognitive function in healthy older adults: implications for desirable tests and period of training.

Previous studies have shown that musical instrument training programs of 16 or more weeks improve verbal memory (Logical Memory Test delayed recall), processing speed (Digit Symbol Coding Test), and executive function (Trail Making Test Part B) of musically untrained healthy older adults. However, it is unclear whether shorter-period instrument training can yield similar effects. We sought to (1) verify those results and (2) clarify if intervention effects could be detected using other measures such as reaction time. Healthy older adults (mean age = 73.28 years) were pseudo-randomly assigned to an untrained control group (n = 30) or an intervention group (n = 30) that received a weekly 10-session musical instrument training program (using melodica). We conducted neuropsychological tests on which intervention effects or association with musical training were reported in previous studies. We newly included two reaction time tasks to assess verbal working memory (Sternberg task) and rhythm entrainment (timing task). Intervention effects were determined using a "group × time" analysis of variance (ANOVA). The intervention effects were detected on the reaction time in Sternberg task and phonological verbal fluency. Although intervention effects had been reported on Logical Memory test, Digit Symbol Coding Test and Trail Making Test in previous studies with longer training periods, the present study did not show such effects. Instead, the test-retest practice effect, indicated by significant improvement in the control group, was significant on these tests. The present results indicated the usefulness of working memory assessments (Verbal Fluency Test and Sternberg task) in detecting the effects of short-term melodica training in healthy older adults. The practice effect detected on those three tasks may be due to the shorter interval between pre- and post-intervention assessments and may have obscured intervention effects. Additionally, the findings suggested the requirement for an extended interval between pre- and post-tests to capture rigorous intervention effects, although this should be justified by a manipulation of training period.

ASSESSMENT OF ECONOMIC WORTH OF GREEN ROOF: A CASE STUDY IN PUTRAJAYA

The current global temperature rise has affected local climate change issues and increased the energy usage for the building cooling process. Following this, the roof components have been identified to contribute the building heating effect due to exposure for more than 10 hours a day which at the same time secretes 70% of the sun's radiation. As an alternative, the green roof concept approach potentially reduces the effects of internal heat and operating costs of cooling the building while providing an investment return for the desired period. This study aims to measure the level of effectiveness of the building green roof concept on the building cooling rate and its profitability implications. Two objectives have been set. First, to compare the effects of concrete and green roof applications on energy consumption and operating costs for the cooling effects of air-conditioned buildings (active systems). Second, to evaluate the maintenance cost and profitability of applying the green-roofed building concept in terms of periodic return on investment. The findings of this study are seen to help the government and relevant agencies consider using the green roof concept in the physical construction of buildings in the future.

A novel routing protocol for underwater wireless sensor networks based on shifted energy efficiency and priority

Underwater Wireless Sensor Networks (UWSNs) are among the most promising research areas these days due to their unique characteristics and diverse underwater applications. Though a number of routing protocols have been designed and implemented for UWSNs over the past few years, the researchers face several challenges, e.g., low speed of propagation, small bandwidth, limited battery power, etc., while designing routing protocols for communication in UWSNs. Acoustic sensor nodes are equipped with batteries with limited power and it is quite costly to replace or recharge them. The network will not survive for the desired period of time if the power of node batteries is not efficiently used. To effectively resolve this issue, this paper proposes a Shifted Energy Efficiency and Priority (SHEEP) routing protocol for UWSNs. The proposed protocol aims to enhance the efficiency of the state-of-the-art Energy Balanced Efficient and Reliable Routing (EBER2) protocol for UWSNs. SHEEP is built upon the depth and energy of the current forwarding node, the depth of the expected next forwarding node, and the average energy difference among the expected forwarders. Simulation results demonstrate that SHEEP improves the energy efficiency and packet delivery ratio in comparison to EBER2 by 7.4% and 13% respectively.

Changes in Seizure Frequency and Characteristics During COVID-19 Pandemic: A Hospital-based Study

Background: It was found that the novel coronavirus disease 2019 (COVID-19) pandemic contributed to changes in the epidemiologic and symptomatic pattern of some neurologic disorders. Objectives: The present study investigated the frequency of seizures and their characteristics from February to August 2020 (the peak of the COVID-19 pandemic) compared to the same period the year before. Materials & Methods: This cross-sectional-analytical study was performed on patients with seizures in Poursina hospital in Guilan province, Iran, between February and August 2020 and the same period the year before. Patients with seizures at the beginning or during hospitalization with at least one seizure in the desired period were included in the study. Results: The increase in seizure frequency during the COVID-19 pandemic versus last year was statistically significant (P=0.014). It also observed a significant difference in seizure etiology (P=0.032), types (P<0.005), and history of seizure (P<0.001). The most prevalent causes of seizures and stroke before and during the COVID-19 pandemic are unknown. The convulsive status epilepticus increased during the COVID-19 pandemic period by 4-fold. Before the pandemic, the patients had a higher prevalence of seizure history. Conclusion: The frequency of seizures, their types, and etiology changed during the COVID-19 pandemic, signifying that COVID-19 can influence on hospital burden of the seizure population.

Twisted memories: Addiction-related engrams are strengthened by desire thinking

Associative learning plays a central role in addiction by reinforcing associations between environmental cues and addiction-related information. Unsupervised learning models posit that memories are adjusted based on how strongly these representations are coactivated during the retrieval process. From a different perspective, clinical models of addiction posit that the escalation and persistence of craving may depend on desire thinking, a thinking style orienting to prefigure information about positive addiction-related experiences. In the present work, we tested the main hypothesis that desire thinking is a key factor in the strengthening of addiction-related associations. A group of adult smoking volunteers (N = 26) engaged in a period of desire thinking before performing an associative learning task in which neutral words (cues) were shown along with images (smoking-related vs. neutral context) at different frequencies. Two retrieval tests were administered, one immediately after encoding and the other after 24 h, to test how the recall of associations changed as a function of retention interval. Two control groups, smokers (N = 21) and non-smokers (N = 22), performed a similar procedure, with a neutral imagination task replacing desire thinking. Participants who engaged in desire thinking increased their performance from the first to the second retrieval test only for the most frequent smoking-related associations. Crucially, this selective effect was not observed in the two control groups. These results provide behavioral evidence in support of the idea that desire thinking plays a role in strengthening addiction-related associations. Thus, this thinking process may be considered a target for reconsolidation-based conceptualizations of, and treatments for, addiction.

Optimal hysteresis of shape memory alloys for eliminating seismic pounding and unseating of movement joint systems

Bridge structures adapt to movement through the addition of joint systems that accommodate anticipated movement due to temperature variations or earthquakes, thereby relieving stress on the bridge structure. Shape memory alloys (SMAs) have been proposed to limit joint displacements because of their ability to dissipate seismic energy and restore their original shape. A parametric study is conducted in this study using computer simulations of some advanced MATLAB programs to show the effects of all hysteretic parameters of SMA retrofit devices on seismic joint openings. The results show that SMA hysteretic parameters have a huge effect on SMA efficiency as a restrainer, which is compatible with energy dissipation philosophy, but there are some reversible impacts of some hysteretic parameters in some cases due to the resonance problem and their dependence on other parameters such as natural time period, period ratio, mass ratio, and seismic records. As a result, some design charts are created in this study after more than 200 million trials, taking into account the variation of all key parameters of the structure and the SMA under a suite of historical ground motion records. Moreover, bridge designers can choose optimal SMA hysteresis for a desired opening width, a desired time period, and desired period/mass ratios between adjacent frames with the help of these charts to overcome the two bridge problems of pounding and unseating of bridge decks.

Optimization of Heat Pump Systems in Buildings by Minimizing Costs and CO2 Emissions

District heating systems are gaining global recognition as an essential tool for reducing greenhouse gas emissions and transitioning to a low-carbon-energy future. In this context, heat pumps are becoming an important technology, providing an effective solution for improving energy efficiency and reducing the reliance on fossil fuels in heating systems. Therefore, this study is focused on the optimal selection of heat pump systems for different types of buildings considering technical, economic, environmental, and social factors. This paper proposes a novel methodology based on mixed-integer nonlinear programming and multi-objective optimization that minimizes total costs and reduces CO2 emissions for heat production and supply systems over a desired period. The methodology is applied to various building types, including renovated and unrenovated apartment buildings, schools, kindergartens, and a supermarket. The study analyzes various types of heat pumps and electric heaters for space heating and domestic hot water production. Optimization results showed that the optimal heating system includes air-to-water heat pumps and electric heaters. Furthermore, for schools and a supermarket, these systems are combined with hybrid heat pumps. The goal of making the heating system neutral in terms of CO2 emissions was achieved for eight out of eleven buildings analyzed. The most profitable investments were in the heating systems of renovated five-story and unrenovated nine-story apartment buildings due to their low energy costs (0.0831 EUR/kWh), short payback periods, and high returns on investment.

A new framework for ground motion selection for structural seismic assessment

Performance-based structural seismic assessment generally requires the selection of ground motions wherein the target acceleration response spectrum (Sa) should be matched in a desired period range. The pros and cons of the commonly used uniform hazard spectrum (UHS), conditional mean spectrum (CMS) and conditional spectrum (CS) are thoroughly examined. Aiming at combining the merits and overcoming the challenges of these methods, a new framework is proposed to construct a series of conditional target spectra for selecting ground motions. The response spectrum is expressed as the product of peak ground acceleration (PGA) and the normalized spectra (β = Sa/PGA) which can be smoothed by four spectral shape parameters. The proposed framework provides the expected median and covariance of the spectral shape parameters conditioned on specified design values of PGA and PGV/PGA (peak ground velocity/PGA). Efficient step-by-step procedures are developed for the application of the proposed alternative approach, and a sample application is illustrated and compared with the CS approach. It is demonstrated that the proposed methodology is capable of incorporating conventional probabilistic seismic hazard analysis (PSHA), considering spectral shape and spectral variability of realistic ground motions while avoiding the choice of the conditioning period. Site class effects can also be incorporated into the proposed approach.

Fictitious time integration method for seeking periodic orbits of nonlinear dynamical systems

In the paper, we compute the period and periodic orbit of an n-dimensional nonlinear dynamical system by developing two iterative algorithms based on the fictitious time integration method (FTIM). Periodicity condition, also known as the Poincaré map, is a necessary condition for the existence of a periodic motion in the state space, which consists of n implicit nonlinear algebraic equations (NAEs). Instead of solving the NAEs by the Newton–Raphson method, we derive an equivalent nonlinear scalar equation to determine unknown period by using the FTIM. The resulting sequence of the iterated periods monotonically converges to a desired period, wherein the unknown initial point on the periodic orbit is determined simultaneously. We find that the second iterative algorithm using the matrix shape function to convert the periodic problem into a corresponding initial value problem is convergent faster than the first iterative algorithm. A key point is that the periodicity condition is satisfied automatically by the second iterative algorithm when the terminal values of the new variables are convergent. Numerical examples exhibit some major advantages of these two iterative algorithms.

Simulation Analysis and Experiments for Blade-Soil-Straw Interaction under Deep Ploughing Based on the Discrete Element Method

The desirable sowing period for winter wheat is very short in the rice-wheat rotation areas. There are also lots of straw left in harvested land. Deep rotary tillage can cover rice straw under the surface to increase soil organic matter. Clarifying the effect of the rotary tillage blade on the soil and straw, as well as analyzing the movement patterns and forces on the straw and soil, are essential to investigate the deep rotary tillage process in order to solve the problems of energy consumption and poor straw burial effect of deep tillage and deep burial machinery. In this study, we built the interaction model of rotary blade-soil-straw through the discrete element method to conduct simulation and identified the factors that affect the power consumption and operation quality of the rotary blade. The simulation process reflects the law of rotary blade-soil-straw interaction, and the accuracy of the simulation model has been verified by field trials. The simulation test results show that the optimized structural parameters of the rotary tillage blade were 210 mm, 45 mm, 37° and 115° (R, H, α and β) designed based on this theoretical model can cultivate to a depth of 200 mm. The operating parameters were 8π rad/s for rotational speed and 0. 56 m/s for forward speed, respectively; the simulated and field comparison tests were conducted under the optimal combination of parameters, and the power, soil breaking rate, and straw burial rate were 1.73 kW, 71.34%, and 18.89%, respectively; the numerical error rates of simulated and field test values were 6.36%, 5.42%, and 8.89%, respectively. The accuracy of the secondary model was verified. The simulation model had good accuracy at all factor levels. The model constructed in this study can provide a theoretical basis and technical reference for the interaction mechanism between rotary tillage and soil straw, the optimization of machine geometry, and the selection of operating parameters.

An autonomous, multi-agent, IoT-empowered space logistics system for mission-critical inventory packing

In recent aerospace missions, space logistics have proven essential in storing, delivering and returning crew and materials between terrestrial facilities and space stations. Unlike classical commercial logistics, space logistics operations are cost-prohibitive and mission-driven, and its replenishment cycle for essential materials is relatively long. Therefore, the complete utilisation of spacecraft payload is of utmost importance. The theory of the inventory packing problem is extended in this study to build autonomous agents that interact with one another within a space logistics decision support system to reinforce the replenishment decision, chunk loading optimisation, and quality inspection. With the long replenishment cycle time, an agent embedded with interval type-2 fuzzy logic is explored to support chaotic time-series demand forecasting to derive re-order quantities in the desired period. Afterwards, the second agent solves the space chunk loading problem using the differential evolution algorithm to utilise payloads and capacities, particularly cylindrical chunks fully. The third agent measures actual item dimensions and quality to deploy the three-dimensional object scanning devices. Feedback is provided to the second agent to derive optimal chunk-loading instructions. Thanks to the autonomous interactions among the above agents, mission-critical decisions for space logistics are supported to achieve operational excellence.

A bioresorbable peripheral nerve stimulator for electronic pain block.

Local electrical stimulation of peripheral nerves can block the propagation of action potentials, as an attractive alternative to pharmacological agents for the treatment of acute pain. Traditional hardware for such purposes, however, involves interfaces that can damage nerve tissue and, when used for temporary pain relief, that impose costs and risks due to requirements for surgical extraction after a period of need. Here, we introduce a bioresorbable nerve stimulator that enables electrical nerve block and associated pain mitigation without these drawbacks. This platform combines a collection of bioresorbable materials in architectures that support stable blocking with minimal adverse mechanical, electrical, or biochemical effects. Optimized designs ensure that the device disappears harmlessly in the body after a desired period of use. Studies in live animal models illustrate capabilities for complete nerve block and other key features of the technology. In certain clinically relevant scenarios, such approaches may reduce or eliminate the need for use of highly addictive drugs such as opioids.

Thermal energy storage for increased waste heat recovery at a silicon production plant in Norway

• Case study of a heat recovery system in a Norwegian silicon production plant. • Novel field of application for Ruths steam accumulator. • Combined approach of techno-economic optimization and dynamic system simulation. • Thermal storage increases annual electricity production by up to 500 MW h. • Public funds required to achieve desirable payback periods. The production of silicon is an energy-intensive process, which requires high temperatures. Sudden release of high-temperature gas to the exhaust system is an inevitable part of silicon furnace operation and causes strong fluctuations in the waste heat recovery system. This makes waste heat recovery challenging and leads to frequent throttling of the produced steam reducing the efficiency of the system. To avoid this throttling and thus increase system efficiency, retrofitting a thermal energy storage to the existing waste heat recovery system is analyzed for a silicon production plant in Norway. A steam accumulator installed in parallel to existing bypasses, which does not interfere with the existing waste heat recovery system, is found to be ideally suited for the case. The analysis is carried out using real plant data, which is used to calibrate a dynamic simulation model modelled in the Modelica language. Design parameters of the steam accumulator are identified based on economic optimizations and their performance is verified with the dynamic simulation model. The simulation results shows that the simplifications in the economic optimizations are acceptable and that storage sizes of less than 10 m 3 can lead to annual profits of around 23 k€. Investment costs excluding transport and on-site installation are around 120 k€, yielding payback times from three to six years, depending on public funds. Including transport and on-site installation increases the payback times to about seven to ten years. The integration of a storage of this size was deemed realistic by the plant operators. The results will therefore be used for the creation of a business case with a more detailed cost analysis.

Energy flexibility of space-heating or cooling in Spain based on Developed Wildebeest Herd Optimization algorithm

The present study analyzes the feasibility of energy flexibility for space cooling and heating of a typical Spanish domestic building during dissimilar geographical conditions. This study uses a new modified metaheuristic algorithm, called the Developed Wildebeest Herd Optimization (DWHO) algorithm to improve the demand for thermostat settings. The algorithm is also decreasing the network interaction and the costs of the operation. The main reason for using the proposed DWHO algorithm is to improve the accuracy of the algorithm and also to resolve the problem of convergence speed. The study also analyzes the Expected Flexibility Savings Index (EFSI) score. Simulation results indicated that the utilized energy flexibility indicator depends on different factors, such as electricity tariffs utilization time; thermal inertia of the typical domestic, and geographical position of the building users’ comfort boundaries. Simulations are established during a 24-h period. Simulation shows that the largest potential is achieved by Algezares with better irradiation capability. Alternatively, available cost flexibility in summer is decreased as the outside temperatures. Results show that the operation cost saves well. The final results indicate that the flexibility value is improved when the PV has been added to the system. This is proved based on the penalty factor. This shows that the proposed approach unites any desired period and can be used as an efficient planning tool for the policymakers.