Alejandro H. Espera

Studies on deep soil mixing (DSM) are often highly site-specific, which focuses on specific in-situ soil conditions and desired project specifications. Although hundreds of studies have already been published, there is no consolidated body of knowledge that will serve as a reference for future DSM projects. This study presents a scoping review of the applications of deep soil mixing (DSM) for soft soil improvement in East and Southeast Asia. A total of 30 peer-reviewed studies published from 2010–2025 were analyzed following the PRISMA-ScR framework. Data were extracted according to the inclusion and exclusion criteria and were systematically organized into different classifications. The results show that DSM is commonly applied in soft and marine clay, with ordinary Portland cement as the primary binder. Wet-mixing techniques and column-based configurations were the most widely used approaches. Documented improvements show an increase in unconfined compressive strength from approximately 200 kPa to 3000 kPa, a decrease in settlement of up to 97.45%, and increases in bearing capacity of up to 169%, depending on the column arrangement and soil conditions. However, test methods in the majority of the studies focus more on laboratory experiments and software simulations, which reflect a consistent discrepancy between the field and laboratory performance of soils, with field strengths reported to be 15–55% lower. Minimal resources were gathered from countries such as the Philippines, and the overall trend in the type of soil studied leans toward clay-based soils rather than organic soils such as peat. Overall, this study concluded that DSM is an effective method in improving the qualities of soft soil. Further studies regarding DSM must focus on field-based investigations, develop a standardised design manual, and assess its long-term quality performance.

Contribution: This article presents a mixed-methods study of generative AI assistance in graduate engineering paper critiques and operationalizes AI distortion as a validity problem in writing-based assessment. Background: Generative AI can improve fluency and organization, but it may also encourage overreliance, homogenized academic expression, cognitive offloading, and weakened assessment validity. Research Questions: The study asks how rubric performance, AI-writing indicators, and feedback-coded reasoning markers differ across AI-permitted and AI-prohibited critique phases. Methodology: A convergent mixed-methods design was applied to 120 anonymized critique records from a graduate sustainable-energy course. Results: AI-permitted critiques scored substantially higher than AI-prohibited critiques across all rubric domains, while qualitative feedback indicated that surface polish sometimes masked reduced methodological specificity and source fidelity. Conclusion: The results support a sociocognitive validity interpretation: AI can scaffold communication but may distort the evidentiary meaning of written critique artifacts when the intended construct is graduate-level disciplinary reasoning.

This paper presents the design and performance evaluation of a LoRa-based vehicle tracking system, emphasizing its hardware architecture and field performance. The system uses custom-built end nodes equipped with Heltec WiFi LoRa 32 (V3) microcontroller boards (integrating an ESP32 microcontroller and SX1262 LoRa transceiver) and NEO-6M GPS modules, which transmit real-time location data to a centrally located LoRa receiver node. Unlike typical cloud-integrated LoRaWAN solutions, this network operates in a standalone point-to-point topology with a local database server, thereby eliminating the need for external network infrastructure. We detail the hardware integration of the LoRa radio, GPS, and antenna design, including a compact enclosure for in-vehicle units and a high-placement antenna for the central receiver. Multiple transmission schemes were implemented to coordinate multiple vehicles: fixed-interval broadcasting, randomized interval transmissions, and a beacon-synchronized TDMA protocol for collision avoidance. Field tests were conducted in both a suburban open road and a dense urban downtown area to benchmark range, signal quality, and packet delivery reliability under varied propagation conditions. The hardware achieved robust long-range communication up to ~ 4.5 km in suburban line-of-sight conditions, while urban coverage reached approximately 1.0–1.5 km due to building obstructions. The measured Received Signal Strength Indicator (RSSI) levels and Packet Delivery Rate (PDR) are analyzed for each environment: in suburban trials RSSI remained above − 100 dBm up to ~ 700 m and PDR averaged ~ 85–90%, whereas in urban trials RSSI fell off faster (e.g. -107 dBm at 700 m) and PDR ranged ~ 70–80%, with occasional drops to ~ 64% in the most obstructed scenarios. The results demonstrate that a bespoke LoRa hardware platform with local data handling can serve as a low-power, cost-effective alternative to cellular or LoRaWAN-based trackers for vehicular applications. We discuss hardware-oriented optimizations, including antenna elevation and transmission scheduling, which improved reliability. Overall, the proposed system demonstrates the feasibility of a standalone LoRa network for real-time vehicle tracking while highlighting remaining challenges in urban RF performance and scalability across multiple nodes.

Battery selection for renewable energy storage is a technology-choice problem rather than a simple comparison of nominal capacity or purchase price. Here, we quantitatively compare lead-acid, a nickel-metal hydride cell, and LiFePO₄ using common-load discharge testing, LiFePO₄ load-resistance optimization, and linked lifecycle and sustainability interpretation. Under identical discharge conditions, LiFePO₄ retained the highest operating voltage and the longest discharge duration, whereas lead-acid showed the shortest useful discharge, and the nickel-metal hydride cell remained intermediate. The optimization dataset further showed that maximum measured LiFePO₄ power occurred at the lowest tested resistance, consistent with low internal resistance and favorable high-rate operation. When these results are interpreted together with replacement frequency, maintenance, recyclability, and environmental trade-offs, LiFePO₄ emerges as the most defensible option for repeated-use renewable energy storage applications, while lead-acid remains relevant where mature recycling infrastructure and low upfront cost dominate decision-making. The analysis, therefore, moves beyond a simple chemistry ranking and offers a technology-level framework for battery selection under the practical constraints of renewable energy deployment.

When a polypropylene drainage geocomposite is specified for a retaining wall or a landfill drainage blanket, the flow capacity reported on the product data sheet is often obtained under hydraulic and confinement conditions that differ from field service. This mismatch is not a minor calibration issue because it can shift the apparent factor of safety by more than threefold. This technical note examines that problem using a manufacturer-supplied EN ISO 12958 dataset comprising 72 observations across two core thicknesses (5 and 10 mm), two hydraulic gradients (0.10 and 1.0), and two seating pressures (200 and 500 kPa), combined factorially to yield eight treatment combinations. Flow capacity and transmissivity (θ = q/i) are reported for all treatment combinations and interpreted against the allowable-flow frameworks of GRI GC8 and ASTM D7931. The 10 mm core at gradient 1.0 delivered about 3.9 times the flow of the same core at gradient 0.10, not the tenfold increase implied by Darcy-type proportionality. Average transmissivity decreased consistently with increasing gradient, indicating transition to a non-laminar in-plane flow regime at i = 1.0. The flow reduction from 200 to 500 kPa reached 3.3-fold for the 10 mm core under the steeper gradient, large enough to invalidate specifications anchored to low-pressure catalog data. Practical guidance is provided for retaining-wall backfill drains, landfill drainage blankets, and pavement subdrainage layers.