Olfactory function following open rhinoplasty: A 6-month follow-up study

<p>Abstract</p> <p>Background</p> <p>Patients undergoing any type of nasal surgery may experience degrees of postoperative olfactory dysfunction. We sought to investigate "when" the olfactory function recovers to its preoperative levels.</p> <p>Methods</p> <p>In this cohort design, 40 of 65 esthetic open rhinoplasty candidates with equal gender distribution, who met the inclusion criteria, were assessed for their olfactory function using the Smell Identification Test (SIT) with 40 familiar odors in sniffing bottles. All the patients were evaluated for the SIT scores preoperatively and postoperatively (at week 1, week 6, and month 6).</p> <p>Results</p> <p>At postoperative week one, 87.5% of the patients had anosmia, and the rest exhibited at least moderate levels of hyposmia. The anosmia, which was the dominant pattern at postoperative week 1, resolved and converted to various levels of hyposmia, so that no one at postoperative week 6 showed any such complain. At postoperative week six, 85% of the subjects experienced degrees of hyposmia, almost all being mild to moderate. At postoperative six month, the olfactory function had already reverted to the preoperative levels: no anosmia or moderate to severe hyposmia. A repeated ANOVA was indicative of significant differences in the olfactory function at the different time points. According to our post hoc Benfronney, the preoperative scores had a significant difference with those at postoperative week 1, week 6, but not with the ones at month 6.</p> <p>Conclusion</p> <p>Esthetic open rhinoplasty may be accompanied by some degrees of postoperative olfactory dysfunction. Patients need a time interval of 6 weeks to 6 months to fully recover their baseline olfactory function.</p

A Charge/Discharge Plan for Electric Vehicles in an Intelligent Parking Lot Considering Destructive Random Decisions, and V2G and V2V Energy Transfer Modes

The random decisions of electric vehicle (EV) drivers, together with the vehicle-to-vehicle (V2V) and vehicle-to-grid (V2G) energy transfer modes, make scheduling for an intelligent parking lot (IPL) more complex; thus, they have not been considered simultaneously during IPL planning in other studies. To fill this gap, this paper presents a complete optimal schedule for an IPL in which all the above-mentioned items are considered simultaneously. Additionally, using a complete objective function&mdash;including charging/discharging rates and prices, together with penalties, discounts, and reward sets&mdash;increases the profits of IPL and EV owners. In addition, during peak times, the demand for energy from the distribution system is decreased. The performance of the proposed schedule is validated by comparing three different scenarios during numerical simulations. The results confirm that the proposed algorithm can improve the IPL&rsquo;s benefits up to USD 1000 and USD 2500 compared to the cases that do not consider the V2V and V2G energy transfer modes, respectively

A Charge/Discharge Plan for Electric Vehicles in an Intelligent Parking Lot Considering Destructive Random Decisions, and V2G and V2V Energy Transfer Modes

The random decisions of electric vehicle (EV) drivers, together with the vehicle-to-vehicle (V2V) and vehicle-to-grid (V2G) energy transfer modes, make scheduling for an intelligent parking lot (IPL) more complex; thus, they have not been considered simultaneously during IPL planning in other studies. To fill this gap, this paper presents a complete optimal schedule for an IPL in which all the above-mentioned items are considered simultaneously. Additionally, using a complete objective function—including charging/discharging rates and prices, together with penalties, discounts, and reward sets—increases the profits of IPL and EV owners. In addition, during peak times, the demand for energy from the distribution system is decreased. The performance of the proposed schedule is validated by comparing three different scenarios during numerical simulations. The results confirm that the proposed algorithm can improve the IPL’s benefits up to USD 1000 and USD 2500 compared to the cases that do not consider the V2V and V2G energy transfer modes, respectively

Relationship between Brain Lesion Location and Aphasia Type in Persian Speaking Patients with Stroke

Objective: It has been many years that brain lesion analysis of different aphasia Syndromes has led the foundation to investigate the language representation and organization in the brain. The aim of this study was to examine the relationship between brain lesion location and Broca's aphasia and Wernecke's aphasia in Persian speakers with stroke. Materials & Methods: In a single system design study, from 120 patients with stroke attending Emam Khomeyni and Loghman hospitals, Rofeyde, Karaj neurology, and Tabassom speech clinics and according to the Farsi Aphasia Test (FAT), syntactic comprehension subscale of Bilingual Aphasia Test (BAT), Farsi Aphasia Naming Test, and Apraxia Assessment inventory, only 9 patients with Broca’s aphasia and 2 with Wernicke’s aphasia were qualified to participate in this study. Patients’ brain lesion sites were determined by MRI. Patients with Broca’s aphasia were 5 male and 4 female Wernecke’s aphasia patients were 2 male. Results: External capsule-insula, rolandic operculum, inferior frontal gyrus, (precentral gyrus and postcentarl gyrus), and the anterior part of temporal gyrus were damaged in Broca’s aphasia patients (64±12.51 years old) and the lesions of external capsule-insula, posterior part of temporal gyrus, anterior part of temporal gyrus, inferior parietal lobule were observed in Wernicke’s aphasia patients (66±8.48 years old). Conclusion: In no patient with Broca’s aphasia or Wernicke’s aphasia brain lesion confined only to Broca’s area or Wernicke’s area respectively. However, due to the limited number of participants in the present study, the extrapolation of the findings to other subjects with Broca’s or Wernicke’s aphasia would certainly be difficult

Probabilistic Optimization of Networked Multi-Carrier Microgrids to Enhance Resilience Leveraging Demand Response Programs

Microgrids have emerged as a practical solution to improve the power system resilience against unpredicted failures and power outages. Microgrids offer substantial benefits for customers through the local supply of domestic demands as well as reducing curtailment during possible disruptions. Furthermore, the interdependency of natural gas and power networks is a key factor in energy systems’ resilience during critical hours. This paper suggests a probabilistic optimization of networked multi-carrier microgrids (NMCMG), addressing the uncertainties associated with thermal and electrical demands, renewable power generation, and the electricity market. The approach aims to minimize the NMCMG costs associated with the operation, maintenance, CO2e emission, startup and shutdown cost of units, incentive and penalty payments, as well as load curtailment during unpredicted failures. Moreover, two types of demand response programs (DRPs), including time-based and incentive-based DRPs, are addressed. The DRPs unlock the flexibility potentials of domestic demands to compensate for the power shortage during critical hours. The heat-power dual dependency characteristic of combined heat and power systems as a substantial technology in microgrids is considered in the model. The simulation results confirm that the suggested NMCMG not only integrates the flexibility potentials into the microgrids but also enhances the resilience of the energy systems

Developing a Robust Expansion Planning Approach for Transmission Networks and Privately-Owned Renewable Sources

Power system restructuring has changed transmission expansion planning (TEP) and caused many complications due to conflicting and contradictory objectives. The transmission capacity expansion would significantly affect the revenue of investor-owned renewable energy sources (RESs). Thus, the investment decisions on merchant RESs must be considered in the TEP studies conducted by the transmission system operator (TSO). In this regard, this paper aims to propose a multi-objective co-planning of investment in transmission networks and merchant RESs with three objective functions: minimizing the investment cost of newly deployed transmission lines, minimizing transmission congestion cost, and minimizing load curtailment in N-1 conditions. Moreover, the TSO guarantees a desirable rate of return for private investors to finance renewable energy projects. Further, a robust optimization (RO) technique is employed to cope with the uncertainties associated with demand and renewable energy production. Also, a posteriori multi-objective optimization algorithm, i.e., the non-dominated sorting genetic algorithm (NSGAII), is applied to solve the advanced optimization problem, followed by the fuzzy min-max method to acquire the final optimal solution. Finally, the IEEE RTS 24-bus test system is utilized to demonstrate the effectiveness and applicability of the suggested approach