Search

Electric truck platooning offers a promising solution to extend the range of electric vehicles during long-haul operations. However, optimizing the platoon speed to ensure efficient energy utilization remains a critical challenge. The existing research on implementing data-driven solutions for truck platooning remains limited and implementing first principles solution is still a challenge. However, recognizing the resemblance of truck platoon data to a time series serves as a compelling motivation to explore suitable analytical techniques to address the problem. This paper presents a novel deep learning approach using a sequence-to-sequence encoder-decoder model to obtain the speed profile to be followed by an autonomous electric truck platoon considering various constraints such as the available state of charge (SOC) in the batteries along with other vehicles and road conditions while ensuring that the platoon is string stable. To ensure that the framework is suitable for long-haul highway operation, the model has been trained using various known highway drive cycles. Encoder-decoder models were trained and hyperparameter tuning was performed for the same. Finally, the most suitable model has been chosen for the application. For testing the entire framework, drive cycle/speed prediction corresponding to different desired SOC profiles has been presented. A case study showing the relevance of the proposed framework in predicting the drive cycle on various routes and its impact on taking critical policy decisions during the planning of electric truck platoons has also been presented. This study would help to efficiently plan the feasible routes for electric trucks considering multiple constraints such as battery capacity, expected discharge rate, charging infrastructure availability, route length/travel time, and other on-road operating conditions while also maintaining stability.

In addition to Power Quality (PQ) problems caused by solid state devices in the distribution side of grid connected Photo Voltaic (PV) system, quality of power also suffers in the source side by the usage of converters. Generally, PQ problems mitigation strategy has turned into a critical issue in grid-connected PV systems. This paper proposes a control topology for PQ issues mitigation scheme in grid connected PV systems. The primary goal of this study is to enhance the PQ in power distribution system through eradicating the voltage interruption, voltage swell and sag as well as voltage fluctuation. To accomplish these changes, Unified Power Quality Conditioners (UPQCs) with controllers were utilized. Then the faults are mitigated by the utilization of UPQC with Tree Seeds Algorithm (TSA) — Adaptive Neuro-Fuzzy Interference System (ANFIS). At first, the normal properties of the grid-connected PV systems are dissected. From that point forward, a few interruptions are made in the system and the abnormal characteristics are analyzed. Then the abnormal characteristics of PQ problems are diminished in the utilization of UPQC and TSA–ANFIS controllers. UPQC is one of the best filters topologies which can mitigate and control all PQ problems. The combined algorithms of TSA-ANFIS are used to keep the dc-link voltage in UPQC at consistent level. The proposed hybrid approach is executed in MATLAB/Simulink platform and the performance is studied. Further, the proposed method is compared with existing Elephant Herding Optimization (EHO) technique and also with hybrid EHO-ANFIS techniques. The comparison results showed that the proposed technique is superior to the EHO and EHO-ANFIS techniques. [ABSTRACT FROM AUTHOR]

The student in adolescent stage faces many problems, and it is more complicated for the students with visual impairment. They need somebody to solve problems in order to avoid tensions and conflicts. Adjustment and personality traits are two important attributes that shape the students into the proper human being. Therefore, this study aims to investigate the adjustment behaviour and its dimensions of visually impaired adolescent students in relation to personality traits. A normative methodology and survey technique has been adopted to a sample of fifty visually impaired students randomly selected from six schools in Namakkal, Salem, Erode, Thiruvannamalai, and Cuddalore districts of Tamil Nadu. The descriptive analysis shows that the level of adjustment behaviour and its dimensions and personality traits were averaged for the whole sample. The differential analysis showed that independent variables onset of blindness, achievement, and birth order did not have a significant influence on the adjustment behaviour. Onset of blindness and achievement has no significant influence, while birth order has a significant influence on the personality traits. The correlation analysis shows that adjustment behaviour has a positive significant relationship with personality traits whereas adjustment dimensions have no significant relationship with respect to personality traits. The stepwise multiple regression analysis shows that birth order is the best predictor that has significant influence on the adjustment behavior. Therefore, the average adjustment behaviour and personality traits of adolescent students with visual impairment need guidance and counseling that is very mandatory to provide a moral support for them to excel in their life.

Overtaking is a complicated maneuver that has implications for the operation and safety of road users on two-lane undivided roads. Understanding the factors influencing the overtaking behavior and process of human drivers becomes essential in the wake of developments in driver awareness, vehicular capabilities, and roadway design. This review classifies the factors which govern the overtaking process of drivers into five categories: vehicle, road, traffic, environment, and driver. Post classification, the effect of each factor based on empirical evidence is discussed on the overtaking behavior of drivers. Based on the analysis, a potential framework is suggested to understand the overtaking process better. Furthermore, future research directions are discussed in the context of modeling approaches, generalizability, connected and automated vehicles, and data collection efforts. [ABSTRACT FROM AUTHOR]

We explore the crystal structure and ionic conductivity of unfilled and cellulose nanowhisker‐filled polymer electrolytes, based on high molecular weight PEO and LiClO4 at a concentration EO:Li = 6:1 (EO = ether oxygen). At this concentration, the polymer electrolyte forms crystalline PEO6 (PEOy—the crystal structure co‐crystallizes "y" PEO ether oxygens to one Li‐anion pair). While the diffraction patterns for PEO3 and PEO6 with LiClO4 are available, their structures are not. Thus, we optimize these structures using density functional theory and show agreement between simulated and experimental diffraction patterns. The PEO6 crystal shows insufficient Li‐ion conductivity due to a lack of percolated conduction paths, and the crystal structure is unstable following 2 months after annealing. Cellulose nanowhiskers, with their patterned surface OH groups, extend the length of PEO6 tunnels, stabilize these tunnels for as long as a year, and result in the percolation of crystals. Although the EO:Li = 6:1 stoichiometry should not favor PEO3 formation, we observe this crystal phase in some unfilled samples. But, with the addition of nanowhiskers, the patterned surface templates PEO6 formation rather than PEO3. Despite these advantages, nanowhiskers do not improve ionic conductivity as hypothesized. The tools developed in this work allow further mechanistic exploration of conduction through crystalline domains. [ABSTRACT FROM AUTHOR]

Metazoan species depict a wide spectrum of regeneration ability which calls into question the evolutionary origins of the underlying processes. Since species with high regeneration ability are widely distributed throughout metazoans, there is a possibility that the metazoan ancestor had an underlying common molecular mechanism. Early metazoans like sponges possess high regenerative ability, but, due to the large differences they have with Cnidaria and Bilateria regarding symmetry and neuronal systems, it can be inferred that this regenerative ability is different. We hypothesized that the last common ancestor of Cnidaria and Bilateria possessed remarkable regenerative ability which was lost during evolution. We separated Cnidaria and Bilateria into three classes possessing whole-body regenerating, high regenerative ability, and low regenerative ability. Using a multiway BLAST and gene phylogeny approach, we identified genes conserved in whole-body regenerating species and lost in low regenerative ability species and labeled them Cnidaria and Bilaterian regeneration genes. Through transcription factor analysis, we identified that Cnidaria and Bilaterian regeneration genes were associated with an overabundance of homeodomain regulatory elements. RNA interference of Cnidaria and Bilaterian regeneration genes resulted in loss of regeneration phenotype for HRJDa , HRJDb , DUF21 , DISP3 , and ARMR genes. We observed that DUF21 knockdown was highly lethal in the early stages of regeneration indicating a potential role in wound response. Also, HRJDa , HRJDb , DISP3 , and ARMR knockdown showed loss of regeneration phenotype after second amputation. The results strongly correlate with their respective RNA-seq profiles. We propose that Cnidaria and Bilaterian regeneration genes play a major role in regeneration across highly regenerative Cnidaria and Bilateria. [ABSTRACT FROM AUTHOR]

Abstract Growth and other dynamical processes in soft materials can create novel types of mesoscopic defects including discontinuities for the second and higher derivatives of the deformation, and terminating defects for these discontinuities. These higher-order defects move “easily", and can thus confer a great degree of flexibility to the material. We develop a general continuum mechanical framework from which we can derive the dynamics of higher order defects in a thermodynamically consistent manner. We illustrate our framework by obtaining the explicit dynamical equations for the next higher order defects in an elastic body beyond dislocations, phase boundaries, and disclinations, namely, surfaces of inflection and branch lines.