Efficient yet realistic ship routing is critical for reducing fuel consumption and greenhouse-gas emissions. However, conventional weather-routing algorithms often produce mathematically optimal routes that conflict with the paths mariners use. This study presents a hybrid approach that constrains physics-based weather routing within an AISderived maritime traffic network (MTN) built from one year of global Automatic Identification System data. The MTN represents common sea lanes as a graph of approximately 10,956 waypoints (nodes) and 17,561 directed edges. Using this network, an optimal low-emission route is computed via graph search and then compared against both a traditional unconstrained route and an advanced weather-routing model (VISIR-2). In a May transitionseason case (Busan–Singapore voyage), the AIS-constrained route reduced fuel consumption and CO₂ emissions by about 1.9% relative to the fastest feasible route, while closely following real traffic corridors (over 90% overlap with actual 2024 AIS tracks). While this 1.9% saving does not reach the high-end potential of an unconstrained, state-of-the-art model like VISIR-2 (which can demonstrate double-digit savings in certain conditions), it is achieved with an increase in transit time of ~6.5 h (≈3.2%). This represents a crucial trade-off, prioritizing operational realism and adherence to real-world traffic corridors over maximum theoretical efficiency.

In an influential paper, Choi and Kim (2010) derived waiting times in an  queuing model under net neurality and under prioritization. In this short paper, we argue that the waiting times of content transmission that Choi and Kim (2010) derived by using the  gueuing model under the non-preemptive priority rule are miscalculated. We provide corrected waiting times in the  queuing model in the prioritization case. We also show that this correction does not affect their main results on the delay time and the incentive to invest in the network capacity qualitatively.

Sensors for monitoring human body movements have gained much attention in the recent times especially in the health-care sector as these devices offer real-time monitoring of vital physiological signs, enabling health-care professionals to evaluate health conditions and provide remote feedback. In this work, we have fabricated carbon-nanotube (CNT)/ polydimethylsiloxane (PDMS) composite sensor through simple dispersion and freezing method for monitoring flexion movements in humans. Sensors with different CNT loadings, namely 0.1 wt %, 0.5 wt %, and 1 wt % were fabricated and analyzed to find the best performing sensor. Several characterizations like Raman, X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), thermogravimetric analysis (TGA), tensile strength measurements, and piezoresistive studies were carried out to study the features of the sensors. Among the fabricated sensors, the one with the loading concentration of 0.5 wt% is found to be most sensitive for flexion applications with higher gauge factor of 533 at 60% strain level, response time of ~ 140 ms and lower hysteresis loss. The feasibility of the sensor for monitoring flexion like finger bending, wrist bending, elbow bending, and knee bending is also analyzed making it ideal for use in sports for athletes, physicians, and trainers to investigate physical performance and well-being.

The most significant threat to the ecosystem is emerging pollutants, which are becoming worse each year and harming the planet severely and permanently. Many organic and inorganic contaminants are present and persistent due to various world events and population growth. As a result, there is a greater need for new technology and its application to address the problems caused by developing pollutants. Carbon composite nanomaterials have significant potential in the fight against numerous environmental contaminants due to their distinctive attributes. This review discusses the reports of customized carbon composite nanomaterials to meet the need for specific elimination of emerging contaminants. Physical and chemical features such as high surface area, conductivity (thermal and electrical), and vibroelectronic properties, size, shape, porosity, and composite nature are making these tailored materials of carbon-based nanomaterials an emerging and sustainable tool to remove persistent compounds like emerging contaminants in aqueous solution. Different composite materials are well discussed in this review, along with their adsorption efficiency of diverse emerging contaminants, including Bisphenol A, estradiol, metformin, etc. This review provides insight into the recent trends limited to 2017–2023. The limitations of carbon-based nanomaterials, such as regeneration and cost-effectiveness, have also been overcome in recent years by diverse modifications in the production process, which can be further improved to make these materials well suited for an extended group of emerging contaminants.

Insect cuticular extracellular matrices (ECM) including the eggshell and exoskeleton play vital roles in protecting them from natural environmental stresses. However, these chitinous ECMs must be degraded at least in part during embryonic and post-embyonic molting periods to accommodate continuous growth all the way to the adult stage. In this study we investigated the functions of groups I and II chitinases, TcCHT5 and TcCHT10, in turnover of the eggshell and cuticle in Tribolium castaneum. RNAi and TEM analyses revealed that TcCHT10 is required for digestion of chitin in the serosal cuticle for embryo hatching as well as in the old cuticle during post-embryonic molts including larval-pupal and pupal-adult metamorphosis. However, although TcCHT5 is apparently involved in these vital physiological events, TcCHT10 could substitute for TcCHT5 except during the pupal-adult molting when both enzymes are indispensable to degrade chitin in the old pupal cuticle.