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A specialized version of collaborative driving is convoy driving. It is referred to as the practice of driving more than one vehicle consecutively in the same lane with a small inter-vehicle distance, maintaining the same speed. Extensive research has been conducted on convoys of heavy-duty trucks on the highway; however, limited research has studied convoy driving in an urban environment. The complex dynamics of an urban environment require short-lived collaboration with varying numbers of vehicles rather than collaborating over hours. The motivation of this research is to investigate how convoy driving can be realized to address the challenges of an urban environment and achieve the benefits of autonomous driving such as reduced fuel consumption, travel time, improved safety, and ride comfort. In this work, the best-fitted coalitional game framework is utilized to formulate the convoy driving problem as a coalition formation game in an urban environment. A hypothesis is formulated that traveling in a coalition is more beneficial for a vehicle than traveling alone. In connection with this, a coalitional game and an all-comprehensive utility function are designed, modeled, and implemented to facilitate the formation of autonomous vehicle coalitions for convoy driving. Multiple solution concepts, such as the Shapley allocation, the Nucleolus, and the Core, are implemented to solve and analyze the proposed convoy driving game. Furthermore, several coalition formation strategies such as traveling mode selection, selecting optimal coalitions, and making decisions about coalition merging are developed to analyze the behavior of the vehicles. In addition to this, extensive numerical experiments with different settings are conducted to evaluate and validate the performance of the proposed study. The experimental results proved the hypothesis that traveling in a convoy is significantly more beneficial than traveling alone. We conclude that traveling in a convoy is beneficial for coalition sizes of two to four vehicles with an inter-vehicle spacing of less than 4 m considering the limitations of an urban environment. Traveling in a coalition allows vehicles to save on fuel, minimize travel time and enhance safety and comfort. Furthermore, the findings of this research state that achieving the enormous benefits of traveling in a coalition requires finding the right balance between inter-vehicle distance and coalition size. In the future, we plan to extend this work by studying the evolving dynamics of the coalitions and the environment.

Limb body wall complex (LBWC) is a complex and rare poly-malformative syndrome. We report a case of this syndrome diagnosed antenatally in a 37-year-old primiparous woman, by a first obstetrical ultrasound performed at 22 weeks of amenorrhea and one day. After termination of pregnancy, macroscopic examination revealed a male newborn with all the diagnostic criteria of LBWC.

The cooperative, connected, and automated mobility (CCAM) infrastructure plays a key role in understanding and enhancing the environmental perception of autonomous vehicles (AVs) driving in complex urban settings. However, the deployment of CCAM infrastructure necessitates the efficient selection of the computational processing layer and deployment of machine learning (ML) and deep learning (DL) models to achieve greater performance of AVs in complex urban environments. In this paper, we propose a computational framework and analyze the effectiveness of a custom-trained DL model (YOLOv8) when deployed in diverse devices and settings at the vehicle-edge-cloud-layered architecture. Our main focus is to understand the interplay and relationship between the DL model’s accuracy and execution time during deployment at the layered framework. Therefore, we investigate the trade-offs between accuracy and time by the deployment process of the YOLOv8 model over each layer of the computational framework. We consider the CCAM infrastructures, i.e., sensory devices, computation, and communication at each layer. The findings reveal that the performance metrics results (e.g., 0.842 mAP@0.5) of deployed DL models remain consistent regardless of the device type across any layer of the framework. However, we observe that inference times for object detection tasks tend to decrease when the DL model is subjected to different environmental conditions. For instance, the Jetson AGX (non-GPU) outperforms the Raspberry Pi (non-GPU) by reducing inference time by 72%, whereas the Jetson AGX Xavier (GPU) outperforms the Jetson AGX ARMv8 (non-GPU) by reducing inference time by 90%. A complete average time comparison analysis for the transfer time, preprocess time, and total time of devices Apple M2 Max, Intel Xeon, Tesla T4, NVIDIA A100, Tesla V100, etc., is provided in the paper. Our findings direct the researchers and practitioners to select the most appropriate device type and environment for the deployment of DL models required for production.

Abstract In this work, a fully integrated active microfluidic device transforming a conventional 96-well kit into point-of-care testing (POCT) device was implemented to improve the performance of traditional enzyme-linked immunosorbent assay (ELISA). ELISA test by the conventional method often requires the collection of 96 samples for its operation as well as longer incubation time from hours to overnight, whereas our proposed device conducts ELISA immediately individualizing a 96-well for individual patients. To do that, a programmable and disposable on-chip pump and valve were integrated on the device for precise control and actuation of microfluidic reagents, which regulated a reaction time and reagent volume to support the optimized protocols of ELISA. Due to the on-chip pump and valve, ELISA could be executed with reduced consumption of reagents and shortening the assay time, which are crucial for conventional ELISA using 96-well microplate. To demonstrate highly sensitive detection and easy-to-use operation, this unconventional device was successfully applied for the quantification of cardiac troponin I (cTnI) of 4.88 pg/mL using a minimum sample volume of 30 µL with a shorter assay time of 15 min for each ELISA step. The limit of detection (LOD) thus obtained was significantly improved than the conventional 96-well platform.

Autonomous vehicles and smart roads are not new concepts and the undergoing development to empower the vehicles for higher levels of automation has achieved initial milestones. However, the transportation industry and relevant research communities still require making considerable efforts to create smart and intelligent roads for autonomous driving. To achieve the results of such efforts, the CCAM infrastructure is a game changer and plays a key role in achieving higher levels of autonomous driving. In this paper, we present a smart infrastructure and autonomous driving capabilities enhanced by CCAM infrastructure. Meaning thereby, we lay down the technical requirements of the CCAM infrastructure: identify the right set of the sensory infrastructure, their interfacing, integration platform, and necessary communication interfaces to be interconnected with upstream and downstream solution components. Then, we parameterize the road and network infrastructures (and automated vehicles) to be advanced and evaluated during the research work, under the very distinct scenarios and conditions. For validation, we demonstrate the machine learning algorithms in mobility applications such as traffic flow and mobile communication demands. Consequently, we train multiple linear regression models and achieve accuracy of over 94% for predicting aforementioned demands on a daily basis. This research therefore equips the readers with relevant technical information required for enhancing CCAM infrastructure. It also encourages and guides the relevant research communities to implement the CCAM infrastructure towards creating smart and intelligent roads for autonomous driving.

Nonspecific distribution and uncontrollable release of drugs in conventional drug delivery systems (CDDSs) have led to the development of smart nanocarrier-based drug delivery systems, which are also known as Smart Drug Delivery Systems (SDDSs). SDDSs can deliver drugs to the target sites with reduced dosage frequency and in a spatially controlled manner to mitigate the side effects experienced in CDDSs. Chemotherapy is widely used to treat cancer, which is the second leading cause of death worldwide. Site-specific drug delivery led to a keen interest in the SDDSs as an alternative to chemotherapy. Smart nanocarriers, nanoparticles used to carry drugs, are at the focus of SDDSs. A smart drug delivery system consists of smart nanocarriers, targeting mechanisms, and stimulus techniques. This review highlights the recent development of SDDSs for a number of smart nanocarriers, including liposomes, micelles, dendrimers, meso-porous silica nanoparticles, gold nanoparticles, super paramagnetic iron-oxide nanoparticles, carbon nanotubes, and quantum dots. The nanocarriers are described in terms of their structures, classification, synthesis and degree of smartness. Even though SDDSs feature a number of advantages over chemotherapy, there are major concerns about the toxicity of smart nanocarriers; therefore, a substantial study on the toxicity and biocompatibility of the nanocarriers has been reported. Finally, the challenges and future research scope in the field of SDDSs are also presented. It is expected that this review will be widely useful for those who have been seeking new research directions in this field and for those who are about to start their studies in smart nanocarrier-based drug delivery. Keywords: Smart drug delivery, Smart nanocarrier, Nanocarrier functionalization, Toxicity of nanocarrier, Cancer cell targeting, Drug release stimulus

In this work, the replication-based microcontact printing method has been presented to study the deformation effect of different printing times and printing pressures on the microcontact printed structures. Cost-effective microcontact printing channels of self-assembled monolayers of alkanethiol have been prepared on gold surface. The alkanethiol inking the polydimethylsiloxanes stamp effectively forms the self-assembled monolayers on the noble gold surface that protects the metal against etchant solution and thereby forms channel-like structures. To address the deformation issue, variations in the printing time in the range of 30 s–60 min and the printing pressure ranging from 840 to 4200 Pa have been studied. The estimation of differing the channel width and channel space with varying printing time and pressure shows the best resolution structures printed under minimal printing time at atmospheric pressure.

Hydrogenated amorphous silicon (a-Si:H) has been effectively utilized as photoactive and doped layers for quite a while in thin-film solar applications but its energy conversion efficiency is limited due to thinner absorbing layer and light degradation issue. To overcome such confinements, it is expected to adjust better comprehension of device structure, material properties, and qualities since a little enhancement in the photocurrent significantly impacts on the conversion efficiency. Herein, some numerical simulations were performed to characterize and optimize different configuration of amorphous silicon-based thin-film solar cells. For the optical simulation, two-dimensional finite-difference time-domain (FDTD) technique was used to analyze the superstrate (p-i-n) planar amorphous silicon solar cells. Besides, the front transparent contact layer was also inquired by using SnO2:F and ZnO:Al materials to improve the photon absorption in the photoactive layer. The cell was studied for open-circuit voltage, external quantum efficiency, and short-circuit current density, which are building blocks for solar cell conversion efficiency. The optical simulations permit investigating optical losses at the individual layers. The enhancement in both short-circuit current density and open-circuit voltage prompts accomplishing more prominent power conversion efficiency. A maximum short-circuit current density of 15.32 mA/cm2 and an energy conversion efficiency of 11.3% were obtained for the optically optimized cell which is the best in class amorphous solar cell. Keywords: Superstrate p-i-n, Power loss, Quantum efficiency, Short circuit current, FDTD

Tailoring optical bandgap of ZnO nanostructured thin films doped with different elements facilitates potential material for photonic applications. Different methods of fabrication process result in different optical and structural properties for the same amount of Mg content. Therefore, details investigation of structural and optical parameters, and their correlation need to be revealed to utilize the fabricated thin films. In this work, Mg-doped ZnO thin film of 200 nm thickness was fabricated by sol-gel spin coating method on a glass substrate for four different Mg content levels. Multiple layers were deposited by a spin coater to increase the film thickness. The prepared thin films were characterized by SEM, XRD, EDS, and UV–Vis spectroscopy. The spectroscopic analysis showed a uniform crystalline nanostructured surface with less structural defects, enhanced transmittance, and higher optical bandgap than that of pure ZnO nanostructured thin film. Change of Mg content from 2% to 8% facilitated tuning of bandgap in the range of 3.30–3.39 eV. Changing trend of structural and optical parameters with Mg content showed non-linear, non-monotonic relation. In-depth analysis of structural and optical properties provides crucial information to form a better view about bandgap dependency on structural parameters. Keywords: Mg-doped ZnO, MgZnO, Bandgap tuning, Sol-gel, Spin coating

This work proposes a modeling of self-assembled monolayers (SAMs) to assess the quality of SAM layers in terms of their leaky behavior. In the modeling, electrochemical impedance spectroscopy (EIS) and a conceptual and simplified resistance-resistance-capacitance (RRC) electrical model from an electrochemical setup were demonstrated. Based on the model, Matlab-based simulation was carried out to find out the suggestive low frequency measurement for analyzing the defective monolayers. Finally, the developed electrical model facilitated the interpretation of the EIS spectra measured in the range of 10 Hz to 100 kHz and provided the capacitance, resistance and thickness of the monolayer. Thus the proposed model could be considered as a powerful tool to characterize the defective SAMs, which was very specific to determine the resistive behavior of the self-assembled monolayers prepared for shorter adsorption time. Keywords: Self-assembled monolayers (SAMs), Octadecanethiol (ODT), Hexadecanethiol (HDT, Impedance, Capacitance of the SAM (CSAM), Resistance of the SAM (RSAM)

Raw material powder mixtures have been prepared with PVC resin, unplasticized polyvinylchloride (uPVC) scrap and additives. A twin screw extruder has been used to make pipe for sample preparation from the mixture. Domestic and external uPVC scrap were formulated and blended with PVC resin to form melt compound. Domestic samples designated as DS-10, DS-20, DS-30, DS-40, DS-50 and DS-100 have been prepared by blending 10, 20, 30, 40, and 50 phr and 100% uPVC domestic scrap with PVC resin and various additives, followed by extrusion, flattening and machining. Following a similar procedure, external samples such as ES-10, ES-20, ES-30, ES-40, ES-50 and ES-100 have been prepared using external uPVC scrap. The effects of the proportions of uPVC scrap in the raw material mix on the mechanical properties such as break stress (BS), % elongation at break, flexural yield strength [1], impact strength (IS) and Shore hardness were investigated. The maximum decrease in break stress is 11.40% for 20 phr domestic scrap, while in samples containing external scrap this decrease is 15.71% for 40 phr scrap. The minimum and maximum reduction in IS values of DS are recorded 1.0% for DS-10 and 27.4% for DS-40, respectively, whereas the minimum and maximum decrease in IS values of ES recorded are 9.6% for ES-10 and 39.2% for ES-50, respectively. The minimum and maximum increase in hardness values of DS are recorded as 0.07% for DS-40 and 2.8% for DS-10, respectively, whereas the minimum and maximum reduction in hardness values of ES are recorded as 1.2% for ES-50 and 2.2% for ES-20, respectively. The mechanical properties of samples were found to deteriorate with increasing quantity of scrap in the raw material mix, the effects of external scrap being more prominent.

Abstract This research was conducted in Toroq Experimental field station, Mashhad, Iran, for two successive cropping seasons (2000-2002), using split plot experimental design based on complete randomized blocks with three replications. Moisture stress treatments (at seven levels) were assigned to main plots, including: D1 ( full irrigation), D2 (no irrigation from one-leaf to double ridge) stage, and in other treatments, no irrigation and preventing rainfall as: D3 (from one-leaf to floral initiation stage), D4 (from floral initiation to the commencement of stem elongation or Terminal spikelet), D5 ( from commencement of stem elongation to flag leaf emergence), D6 (from flag leaf emergence to anthesis) and D7 (from anthesis to the soft dough), and four wheat cultivars, namely: Roshan, Qods, Marvdasht and Chamran, were sown in sub plots. The results of combined analysis of variance showed that the effect of moisture stress was significant. Applying D5, D6 and D7 treatments reduced the grain yield in comparison with control (D1) by 36.7, 22.8 and 45.6, respectively. Severe moisture stress treatments (D5 and D7) caused a reduction in water use efficiency (WUE) and radiation use efficiency (RUE), due mainly to reduction of dry matter. Based on these results, grain filling (D7) and fast growing (D5) stages of wheat were more sensitive to moisture stress. Genotypic differences were also observed with respect to concerned characteristics. Chamran had a higher moisture tolerance, therefore, greater grain yield as compared with the other cultivars. Keywords: Moisture stress; Developmental Stages; Water Use Efficiency; Radiation Use Efficiency; Grain yield

Bioengineered veins can benefit humans needing bypass surgery, dialysis, and now, in the treatment of varicose veins. The implant of this vein in varicose veins has significant advantages over the conventional treatment methods. Deep vein thrombosis (DVT), vein patch repair, pulmonary embolus, and tissue-damaging problems can be solved with this implant. Here, the authors have proposed biomedical microdevices as an alternative for varicose veins. MATLAB and ANSYS Fluent have been used for simulations of blood flow for bioengineered veins. The silver based microchannel has been fabricated by using a micromachining process. The dimensions of the silver substrates are 51 mm, 25 mm, and 1.1 mm, in length, width, and depth respectively. The dimensions of microchannels grooved in the substrates are 0.9 mm in width and depth. The boundary conditions for pressure and velocity were considered, from 1.0 kPa to 1.50 kPa, and 0.02 m/s to 0.07 m/s, respectively. These are the actual values of pressure and velocity in varicose veins. The flow rate of 5.843 (0.1 nL/s) and velocity of 5.843 cm/s were determined at Reynolds number 164.88 in experimental testing. The graphs and results from simulations and experiments are in close agreement. These microchannels can be inserted into varicose veins as a replacement to maintain the excellent blood flow in human legs.

La cuvette synclinale de Kourimat, située dans la partie orientale du bassin d'Essaouira, abrite un aquifere carbonaté constituant l'unique ressource en eau de la région. L'étude entreprise sur cet aquifere a permis de le caractériser de point de vue hydrodynamique, hydrogéologique et hydrogéochimique. La carte piézométrique du systeme montre un sens d'écoulement global du sud-est vers le nord-ouest. Le gradient hydraulique varie de l'amont vers l'aval. Les fluctuations piézométriques montrent une bonne corrélation avec les aléas climatiques. Les résultas de l'étude hydrochimique ont permis de mettre en évidence l'existence de deux nappes: la premiere dans le Cénomanien et l'autre dans le Turonien. Ces deux nappes se différencient par leurs facies chimiques et par l'origine des éléments en solution.

La cuenca sinclinal de Essaouira está constituida por un conjunto de unidades sinclinales, siendo las principales la de Bouabout (en la zona frontal) y la de Essaouira (en la zona trasera). Estas unidades contienen las reservas de agua más importantes de la región que se encuentran en el acuífero Cenomaniense-Turoniense de Bouabout y en los acuíferos del Turoniense y Plio-Cuaternario de la zona sinclinal de Essaouira. El principal río que atraviesa esta cuenca es el denominado Igrounzar (en la zona frontal) y Ksob (en la zona trasera). Es un río perenne gracias a las fuentes Cenomanienses-Turonienses de la zona frontal. Más del 50 % del volumen de agua de este río fluye entre los meses de noviembre y enero. Medidas de aforo diferenciales efectuadas a lo largo del ciclo hidrológico 1990-1991 (Fekri, 1993) demuestran que el Oued Ksob alimenta los acuíferos Plio-Cuaternarios y turoniense por flujos de 42 l/s y 64 l/s, respectivamente. El estudio hidrogeológico de los acuíferos de esta cuenca muestra que las aguas subterráneas fluyen del SE hacia el noroeste en el acuífero Plio-Cuaternario, y hacia el noroeste, el noreste y el oeste a nivel del acuífero Cenomaniense-Turoniense. El estudio hidroquímico permite identificar el origen de las mineralizaciones de las aguas, sus facies y sus calidades. La hidrología isotópica permite estimar las áreas de recarga de los acuíferos y sus interacciones, y definir las relaciones entre las dos unidades que constituyen la cuenca. También muestra que la recarga de los acuíferos por las lluvias eficaces se produce sin una notable evaporación.

Polyglutamine expansions in the transcriptional co-repressor Atrophin-1, encoded by ATN1, cause the neurodegenerative condition dentatorubral-pallidoluysian atrophy (DRPLA) via a proposed novel toxic gain of function. We present detailed phenotypic information on eight unrelated individuals who have de novo missense and insertion variants within a conserved 16-amino-acid "HX repeat" motif of ATN1. Each of the affected individuals has severe cognitive impairment and hypotonia, a recognizable facial gestalt, and variable congenital anomalies. However, they lack the progressive symptoms typical of DRPLA neurodegeneration. To distinguish this subset of affected individuals from the DRPLA diagnosis, we suggest using the term CHEDDA (congenital hypotonia, epilepsy, developmental delay, digit abnormalities) to classify the condition. CHEDDA-related variants alter the particular structural features of the HX repeat motif, suggesting that CHEDDA results from perturbation of the structural and functional integrity of the HX repeat. We found several non-homologous human genes containing similar motifs of eight to 10 HX repeat sequences, including RERE, where disruptive variants in this motif have also been linked to a separate condition that causes neurocognitive and congenital anomalies. These findings suggest that perturbation of the HX motif might explain other Mendelian human conditions.