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Few trucks of the 2000s stirred emotions quite like Scania's T-cab. With its sweeping bonnet and imposing stance, it built a cult following across Europe. Yet 20 years ago Scania pulled the plug. The numbers just didn't add up and the accountants won out over the enthusiasts. It remains one of the industry's great shames, because nothing else on the road has quite the same charisma. The T-cab was about more than hauling freight; it was about pride, identity and turning heads. That demand has never fully gone away.

Since the first cellular networks were trialled in the 1970s, we have witnessed an incredible wireless revolution. From 1G to 4G, the massive traffic growth has been managed by a combination of wider bandwidths, refined radio interfaces, and network densification, namely increasing the number of antennas per site. Due its cost-efficiency, the latter has contributed the most. Massive MIMO (multiple-input multiple-output) is a key 5G technology that uses massive antenna arrays to provide a very high beamforming gain and spatially multiplexing of users and hence increases the spectral and energy efficiency (see references herein). It constitutes a centralized solution to densify a network, and its performance is limited by the inter-cell interference inherent in its cell-centric design. Conversely, ubiquitous cell-free Massive MIMO refers to a distributed Massive MIMO system implementing coherent user-centric transmission to overcome the inter-cell interference limitation in cellular networks and provide additional macro-diversity. These features, combined with the system scalability inherent in the Massive MIMO design, distinguish ubiquitous cell-free Massive MIMO from prior coordinated distributed wireless systems. In this article, we investigate the enormous potential of this promising technology while addressing practical deployment issues to deal with the increased back/front-hauling overhead deriving from the signal co-processing.

Diesel-powered load haul dump machines have been the backbone of underground mining loading and hauling operations for over six decades. However, as mines get deeper, and regulations become more rigorous, the adoption of battery electric vehicles (BEVs) has the potential to enhance energy efficiency and provide a healthier environment for miners. Electric engines have a significantly higher energy efficiency and produce no exhaust gases or diesel particulate matter. The use of BEVs in underground operations introduces additional factors to consider, such as battery swapping and the required number of batteries, swapping, and charging stations. This study conducted a discrete event simulation using Arena simulation software with a focus on queueing and its relationship to different numbers of machines, batteries, and swapping times in an underground block cave mine. The results suggest that when there are six, eight, or 12 LHDs and four swapping and charging stations with an unlimited number of batteries, the queueing time to swap the batteries remains minimal. In scenarios with eight LHDs and a limited number of batteries, depending on the battery swapping time, 2–2.5 batteries per machine are required to achieve maximum production with minimal queueing. However, when there are too few batteries, queueing becomes significant. Moreover, when the number of working groups (machines going for a battery swap around the same time) is less than the ratio between the battery operational time and the swapping time, the queueing remains low.

Live tilapia has seen increased production and demand in the Philippines. Its transport is a rapidly expanding component of commercial fishing and aquaculture industries in the country. Fish dealers need a reliable hauling box to transport the fish at a lower mortality rate. Tilapias are commonly transported using oxygen tanks to supply continuous oxygen in the hauling box. This method has many issues, such as high mortality rate, water quality, and insufficient oxygen supply in higher density of tilapia. This study is about designing and analyzing a modified hauling box that utilizes a piping and filtration system, a diesel pump, and a mechanical filter. A comparative study between the two boxes was conducted in terms of the mortality rate of fish, dissolved oxygen (DO) content, and pH level. It was found that using the modified system yielded an average mortality rate of 0% compared to the traditional, with 14.82%. The DO content for the modified system ranges from 7.5 – 7.9 mg/L, which is higher than the traditional one with 4.6 – 4.8 mg/L. The pH level is closer to neutral values in the modified system, ranging from 7.11-7.21 compared to 6.75-6.84.

Scunthorpe-based Intake Transport, which offers general haulage, heavy haulage and warehousing, has filed notice of its intention to appoint an administrator, in an attempt to save the business from liquidation. The family-led company, which specializes in hauling fabricated steel and carries the strapline Built On Steel on its fleet of over 50 trucks and 100 trailers, was established almost 30 years ago in Jan 1995. Led by brothers and co-directors John and Richard Burgin, Intake Transport has its headquarters in Scunthorpe, South Humberside and also has depots in Sheffield, West Lothian and South Wales.

A battery-powered Mercedes-Benz eActros tractor unit has demonstrated its readiness for UK work by completing a five-day, 1,400-mile journey around the country. Hauling a standard trailer and fully freighted at 40 tonnes, the truck maker said its eActros 600 saw off the challenge at this year's EV Rally event. The saw 50 vehicles of varying sizes and types set off from Oldbury in the West Midlands, on a tour that took in visits to 26 locations corresponding to every letter of the alphabet. Day one involved a 258-mile drive to Carlisle. Day two's route covered 285 miles, ending at the Daimler Truck UK complex at Wentworth Park, near Sheffield. The final stint of 265 miles brought the participants through Wales to the finish line in Chester. Production of the truck will start in December.

The flexible fire hose and net (hose net) is a novel fish-hauling device developed for set-net fishery. The hose net is placed inside the box chamber net, air is injected from one edge of the hose net, the hoses are inflated, and the buoyancy force is increased. The net floats up gradually, cornering the fish on the other edge. In previous studies, we have conducted a series of floating-up and sinking-down experiments to evaluate the performance of the hose net in calm water. In this study, aimed at the practical implementation of the hose net fish-hauling system, we conducted a water tank experiment and a semi-field test to confirm the operation of the hose net, which was installed inside a box chamber net model. The results demonstrated that the net could float up gradually in an ideal form and stretched on the surface of the box net. The time taken to float up processes varied with the air injected into the auxiliary hose and hose net, so that the motion of the hose net could be controlled by adjusting the air at different parts of practical operation. Furthermore, semi-field trials were conducted to verify its performance in the natural marine environment and its ability to capture schools of fish. Overall, this innovative hose net fish-hauling device is expected to be valuable for next-generation set-net fishing.

This research study examines the impact of shifts and lunch breaks on mining operations, particularly focusing on delays in hauling equipment used to supply extracted material to crushers. These delays significantly reduce productivity, averaging below 80% during regular working hours and adversely affecting mine profitability. To address this issue, a Q -learning-based deep reinforcement learning model was developed, utilizing real-world data from mining operations. The model aimed to achieve a 90% coverage in material supply to the crushers. A simulation environment, closely resembling the physical mining setting, was created to test the trucks as agents. Various scenarios, including equipment selection, cycle time, queue times, and material types, were considered. Based on the results, a deep learning model was trained to maximize coverage by determining the optimal combination of trucks and crushers. The solution successfully achieved a 90% supply coverage during shift changes and lunch breaks, with average execution times of less than 1 ms, making it suitable for real-time applications. This research demonstrates the effectiveness of the proposed Q -learning deep reinforcement learning model in optimizing material supply and enhancing mining productivity. By addressing delays and improving operational efficiency, this model holds significant potential for improving profitability in mining operations.

One of the safest types of public transport is the metro, which is actively developing in many countries. Despite a number of advantages, the construction of metro tunnels is a rather labor-intensive process, which involves complex technical equipment in the form of tunnel boring complexes. Tunnel boring complexes include locomotives that perform the functions of hauling away rock using trolley with removable body. Trolley differs from their usual characteristics - in weight, dimensions, as well as the component composition of individual systems, in particular the compressed-air braking system. The article is devoted to the analysis of the parameters of the stress-strain state of one of the main load-bearing elements of a trolley- the casing. As a result of the analysis, design loading cases were selected, the most loaded parts of the body were determined, recommendations were formed for choosing the optimal material thickness of various elements and increasing the load-bearing capacity of the body.