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Recent advances in nanotechnology, including the development of nanoparticles, thin films, and superlattices, have revitalized research in thermoelectricity by enabling independent control of thermal and electrical transport, overcoming longstanding efficiency limitations and expanding opportunities for sustainable energy generation and miniaturized device applications. Tin dioxide (SnO2) has recently attracted increasing attention as a thermoelectric material owing to its properties, such as high-temperature chemical and structural stability, non-toxicity, and the abundance of constituent elements. Current research efforts have been directed toward enhancing its thermoelectric performance through strategies such as elemental doping, nanostructuring, strain engineering, and the development of composite systems. In this study, we investigate the effects of Mg substitutional doping on the thermoelectric characteristics of SnO2. We synthesize undoped and Mg-doped SnO2 nanoparticles (0.05%, 0.10%, and 0.15%) using a straightforward hydrothermal technique. The investigation of the undoped and doped materials revealed that SnO2 possesses a tetragonal rutile-type structure, as determined through structural and morphological examination. The crystalline size of all of the samples decreases as the Mg doping concentration is increased. Hall measurement and Seebeck coefficient measurements have been employed for assessing the thermoelectric characteristics. As the Mg content increased, both the Seebeck coefficient and electrical conductivity value increased from −20 μV/K to −91 μV/K and 29.8 S/cm to 112.6 S/cm, confirming the presence of semiconductor behavior. The 0.15% Mg-doped sample demonstrates the highest power factor when evaluated at a temperature of 150 K, yielding a value of 9.4 × 10−5 WK−2m−1.

Recent advances in nanotechnology, including the development of nanoparticles, thin films, and superlattices, have revitalized research in thermoelectricity by enabling independent control of thermal and electrical transport, overcoming longstanding efficiency limitations and expanding opportunities for sustainable energy generation and miniaturized device applications. Tin dioxide (SnO[sub.2]) has recently attracted increasing attention as a thermoelectric material owing to its properties, such as high-temperature chemical and structural stability, non-toxicity, and the abundance of constituent elements. Current research efforts have been directed toward enhancing its thermoelectric performance through strategies such as elemental doping, nanostructuring, strain engineering, and the development of composite systems. In this study, we investigate the effects of Mg substitutional doping on the thermoelectric characteristics of SnO[sub.2]. We synthesize undoped and Mg-doped SnO[sub.2] nanoparticles (0.05%, 0.10%, and 0.15%) using a straightforward hydrothermal technique. The investigation of the undoped and doped materials revealed that SnO[sub.2] possesses a tetragonal rutile-type structure, as determined through structural and morphological examination. The crystalline size of all of the samples decreases as the Mg doping concentration is increased. Hall measurement and Seebeck coefficient measurements have been employed for assessing the thermoelectric characteristics. As the Mg content increased, both the Seebeck coefficient and electrical conductivity value increased from −20 μV/K to −91 μV/K and 29.8 S/cm to 112.6 S/cm, confirming the presence of semiconductor behavior. The 0.15% Mg-doped sample demonstrates the highest power factor when evaluated at a temperature of 150 K, yielding a value of 9.4 ×10[sup.−5] WK[sup.−2]m[sup.−1].

Recent advances in nanotechnology, including the development of nanoparticles, thin films, and superlattices, have revitalized research in thermoelectricity by enabling independent control of thermal and electrical transport, overcoming longstanding efficiency limitations and expanding opportunities for sustainable energy generation and miniaturized device applications. Tin dioxide (SnO ) has recently attracted increasing attention as a thermoelectric material owing to its properties, such as high-temperature chemical and structural stability, non-toxicity, and the abundance of constituent elements. Current research efforts have been directed toward enhancing its thermoelectric performance through strategies such as elemental doping, nanostructuring, strain engineering, and the development of composite systems. In this study, we investigate the effects of Mg substitutional doping on the thermoelectric characteristics of SnO . We synthesize undoped and Mg-doped SnO nanoparticles (0.05%, 0.10%, and 0.15%) using a straightforward hydrothermal technique. The investigation of the undoped and doped materials revealed that SnO possesses a tetragonal rutile-type structure, as determined through structural and morphological examination. The crystalline size of all of the samples decreases as the Mg doping concentration is increased. Hall measurement and Seebeck coefficient measurements have been employed for assessing the thermoelectric characteristics. As the Mg content increased, both the Seebeck coefficient and electrical conductivity value increased from -20 μV/K to -91 μV/K and 29.8 S/cm to 112.6 S/cm, confirming the presence of semiconductor behavior. The 0.15% Mg-doped sample demonstrates the highest power factor when evaluated at a temperature of 150 K, yielding a value of 9.4 × 10-5 WK m .

Accurate detection of human serum albumin (HSA) is essential for the early diagnosis and monitoring of renal and hepatic disorders. We present a graphene-based electrolyte-gated field-effect transistor (EGFET) for label-free, real-time quantification of HSA under non-Faradaic operation. Devices exploit the high interfacial capacitance of the electric double layer (EDL) to transduce electrostatic perturbations induced by albumin adsorption into measurable conductance modulation. Negatively charged HSA molecules induce systematic modulation of the graphene channel, producing a concentration-dependent displacement of the Dirac voltage consistent with p-type doping. To establish a molecular-level interpretation of the sensing response, Brownian Dynamics simulations show that HSA adsorbs onto graphene through multiple adsorption orientations associated with heterogeneous interfacial charge distributions and variable dipole alignments relative to the surface. Adsorption is energetically stabilized by van der Waals interactions. Analysis of transfer characteristics across concentrations ranging from 0.01 to 30mgmL-1 reveals a correlation between surface charge density and carrier transport modulation within the electric double layer. Optimized devices exhibit a limit of detection of 0.0087 mg mL-1 and a linear dynamic range extending to 10 mg mL-1. The response remains non-Faradaic under sub-volt operation with reversible and reproducible behavior. The use of an inverse-mobility analytical metric highlights the role of disorder-enhanced carrier scattering in signal amplification, enabling sensitive electrostatic detection while preserving reversible device operation. These results establish liquid-gated graphene EGFETs as a promising platform for quantitative protein sensing and provide insight into disorder-mediated transport mechanisms in graphene bioelectronic devices.

Parallel, data-intensive applications are now commonly executed on infrastructures that combine Cloud, Fog, and Edge resources. In these environments, execution takes place on devices with markedly different computational power and over networks whose latency and bandwidth can fluctuate over time. Under these conditions, overall performance is influenced not only by processing speed but also by communication delays arising from data dependencies between tasks. This leads to a basic issue: whether scheduling strategies developed under computation-focused assumptions continue to perform well once communication costs are made explicit. This work examines the behavior of simple and widely adopted scheduling heuristics when network effects are modeled directly within the system. No new scheduling algorithms are introduced. Instead, the analysis focuses on how execution time and monetary cost change for deterministic parallel workloads deployed on hierarchical Cloud–Edge infrastructures exposed to stochastic latency and bandwidth variations. For this purpose, we introduce CLOWNSim, a lightweight discrete-event simulation framework that supports large-scale Monte Carlo experiments on fixed task graphs, allowing infrastructural and scheduling effects to be examined independently of workload variability. The experimental analysis covers fully centralized Cloud deployments, intermediate Fog configurations, and resource-constrained IoT scenarios. Scheduling policies based on computational speed, execution cost, or random device selection are evaluated across these settings. In Cloud and Fog environments, communication latency and data transfers represent a substantial portion of the overall makespan, weakening the impact of scheduling decisions driven primarily by computation. In IoT scenarios, limited processing capacity becomes the main limiting factor, while communication overhead remains present but less influential in comparison. The results indicate that performance trends across the Cloud–Edge continuum cannot be attributed to scheduler choice alone. Execution behavior arises from the combined effects of workload structure, placement decisions, and network properties, with different elements becoming dominant depending on the deployment context. The proposed simulation framework offers a practical way to study these interactions and to assess cost–performance trade-offs under communication conditions that reflect realistic operating environments.

Chromosomal submicroscopic imbalances represent well-known causes of neurodevelopmental disorders. In some cases, these can cause specific autosomal dominant syndromes, with high-to-complete penetrance and de novo occurrence of the variant. In other cases, they result in non-syndromic neurodevelopmental disorders, often acting as moderate-penetrance risk factors, possibly inherited from unaffected parents. We describe a three-generation family with non-syndromic neuropsychiatric features segregating with a novel 19q13.32q13.33 microduplication. The propositus was a 28-month-old male ascertained for psychomotor delay, with no dysmorphic features or malformations. His mother had Attention-Deficit/Hyperactivity Disorder and a learning disability. The maternal uncle had an intellectual disability. Chromosomal microarray analysis identified a 969 kb 19q13.32q13.33 microduplication in the proband. The variant segregated in the mother, the uncle, and the maternal grandmother of the proband, who also presented neuropsychiatric disorders. Fragile-X Syndrome testing was negative. Exome Sequencing did not identify Pathogenic/Likely Pathogenic variants. Imbalances involving 19q13.32 and 19q13.33 are associated with neurodevelopmental delay. A review of the reported microduplications allowed to propose BICRA (MIM *605690) and KPTN (MIM *615620) as candidates for the neurodevelopmental delay susceptibility in 19q13.32q13.33 copy number gains. The peculiarities of this case are the small extension of the duplication, the three-generation segregation, and the full penetrance of the phenotype.

We present the spectroscopic and photometric evolution of the nearby (z = 0.059) spectroscopically confirmed type Ic supernova, SN 2010bh, associated with the soft, long-duration gamma-ray burst (X-ray flash) GRB 100316D. Intensive follow-up observations of SN 2010bh were performed at the ESO Very Large Telescope (VLT) using the X-shooter and FORS2 instruments. Owing to the detailed temporal coverage and the extended wavelength range (3000--24800 A), we obtained an unprecedentedly rich spectral sequence among the hypernovae, making SN 2010bh one of the best studied representatives of this SN class. We find that SN 2010bh has a more rapid rise to maximum brightness (8.0 +/- 1.0 rest-frame days) and a fainter absolute peak luminosity (L_bol~3e42 erg/s) than previously observed SN events associated with GRBs. Our estimate of the ejected (56)Ni mass is 0.12 +/- 0.02 Msun. From the broad spectral features we measure expansion velocities up to 47,000 km/s, higher than those of SNe 1998bw (GRB 980425) and 2006aj (GRB 060218). Helium absorption lines He I lambda5876 and He I 1.083 microm, blueshifted by ~20,000--30,000 km/s and ~28,000--38,000 km/s, respectively, may be present in the optical spectra. However, the lack of coverage of the He I 2.058 microm line prevents us from confirming such identifications. The nebular spectrum, taken at ~186 days after the explosion, shows a broad but faint [O I] emission at 6340 A. The light-curve shape and photospheric expansion velocities of SN 2010bh suggest that we witnessed a highly energetic explosion with a small ejected mass (E_k ~ 1e52 erg and M_ej ~ 3 Msun). The observed properties of SN 2010bh further extend the heterogeneity of the class of GRB supernovae.