bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluation of Mortar Properties Utilizing Partial Cement Substitution with Jarosite
Authors: Gared Om Prakash , Gaur Arun , Khichad Jeetendra Singh , Somani Prakash , Sain Amit 
Published: June 2024

Abstract
This experimental study examines the use of Ordinary Portland Cement 43 grade in combination with jarosite as a partial cement substitute. Various cement pastes were formed, including a control paste without jarosite (J0) and pastes (J5 to J30) with 5%, 10%, 15%, 20%, 25%, and 30% jarosite replacement. The objective of this study is to evaluate the effect of jarosite on the normal consistency, initial setting time, and ultimate setting time of cement paste. Incorporating up to 30% jarosite as a cement substitute significantly increases the normal consistency, initial setting time, and ultimate setting time compared to the control mix by 43.10%, 96.10%, and 22.70%, respectively. The results demonstrate the potential of jarosite as an advantageous replacement material for improving mortar properties. Notably, mixture J15 has the highest compressive strength, measured 37.42 N/mm2 at 7 days and 51.37 N/mm2 at 28 days. Although compressive strength decreases with increasing levels of jarosite replacement, it remains preferable to that of the control mix up to J25.
Valorisation of pond ash as replacement of fine aggregate in cement mortars for practical applications
Authors: Sharma Sandesh , Vyas Ashok Kumar 
Published: June 2024

Abstract
Waste generated during the coal combustion process in thermal power plant is of major concern from disposal point of view. The majority of waste consists of pond ash generated during coal combustion process in thermal power plants. This study aims to use pond ash as a replacement for river sand in cement mortars. The river sand was replaced by pond ash up to 100%, by volume. The mechanical properties were evaluated for 1:4 (cement: sand) mortar mix proportions. The compressive strength of 1:4 mix with 30% replacement of river sand was observed increased by 27%, as compared to control mix. Similarly, tensile bond strength at 30% replacement was increased by 15% as compared to control mix. On the other hand, drying shrinkage was observed to increase by 35% as compared to control mix. Overall, the general mechanical properties like compressive strength, tensile bond strength, adhesive strength, etc. were found to increase up to the replacement of 50% of river sand. Thus, it can be concluded that up to 30% replacement level, almost all the mechanical properties improved.
Impact Resistance of Treated Recycled Aggregate Concrete: Drop Weight Test
Authors: Kumar Amit , Singh Gyani Jail 
Published: June 2024

Abstract
The present study deals with recycled aggregate concrete (RAC) performance against impact loads. The drop weight test determines RAC’s strength and impact energy absorption capacity. Recycled concrete aggregates (RCAs) with different qualities (physical and mechanical properties) are used to prepare the RAC mix. The RAC is treated with three different mechanical treatments with varying charges and drum revolutions. It is observed that quality improvisation in RCA improves RAC impact resistance. A strong correlation between the RCA abrasion value and the RAC impact energy is observed, with an R2 value of 0.79. Additionally, a good correlation holds between the RCA crushing value and the impact energy of RAC with an R2 value of 0.61. Furthermore, RAC’s impact resistance can be enhanced by reducing its brittleness index (BI). The BI of RAC decreases as RCA quality improves. A strong correlation is also held between the BI and the impact energy of RAC with an R2 value of 0.98. The impact energy absorbing capacity of RAC’s with treated RCA is increased by up to 48.35% compared to RAC with untreated RCA. RAC composed with improved quality RCA has an impact energy of 0.92 fractions of natural aggregate concrete (NAC). The impact energy of concrete built from untreated recycled concrete aggregate (URCA) is only 0.62 fraction of the impact energy of concrete made from NA.
A comparative study on life cycle analysis of cold mix and foamed mix asphalt
Authors: Meena Pinki , Ransinchung RN GD , Kumar Praveen 
Published: June 2024

Abstract
Cold mix asphalt (CM) technology is more sustainable and environmentally friendly than hot mix asphalt (HM) technology. The cold mixtures are prepared with aggregates, asphalt emulsion, and water at ambient temperature. The cold mix is used to achieve economic and ecological benefits but is used to a limited extent due to its low strength and high-water sensitivity. Some additives like Ordinary Portland cement, chemical stabilizers, fibers, cement kiln dust, limestone, and fly ash are added to enhance the strength and stability of cold mix asphalt and reduce the susceptibility to moisture. Foamed mix asphalt (FMA) is a unique pavement construction method for enhancing new granular materials. Cold water and air molecules are injected into the Writgen WLB 10S machine’s bitumen expansion chamber to produce foamed bitumen. When hot bitumen mixes with cold water, foam creates, and bitumen bubbles emerge during the instantaneous foaming process, known as foaming. The bitumen collected in a cylindrical bucket during foaming is known as foamed bitumen, and the foamed bitumen is used as a binder during mix design and has a low viscosity. Fundamental indicators of FMA are (i) expansion ratio and (ii) half-life. This paper reflects the life cycle analysis (LCA) of CM to hot mix based on different parameters like energy consumption and carbon emission in the cradle-to-gate stages incorporating the effects of various foaming agent contents. Also, the LCA method estimates greenhouse gas emissions at different stages of production, transport, and pavement laying at the site. The greenhouse gas emission is responsible for global warming.
Use of Sustainable Material as Column Filler in Soft Clay Bed Reinforced with Stone Column: Numerical Study
Authors: Srijan  , Somra Kevin , Kharra Pooja , Singh Sagar 
Published: June 2024

Abstract
Soil reinforcement is technique to improve the engineering characteristics of soil. For stabilizing the problematic soils (soft clay), a number of strengthening techniques are available, including the employment of thermal techniques, portland cement, lime, fly ash, ground freeing, jet grouting, and prefabricated vertical drains. Similarly, one of the most popular procedures for improving soil is using stone columns, which have been used all over the world to improve structures built on soft clay by increasing their bearing capacity and lowering total and differential settlements. Consolidation is accelerated by the function of stone columns as vertical drains. In this paper, Steel slag, an industrial waste, is used as a column filler material, which can act as a sustainable material and will also address the current environmental concern. Using steel slag for soil stabilization can be an economical and ecologically conscious way to extract solid waste. To explore the various behavioural responses of virgin soft clay beds and clay beds built with stone columns, a numerical analysis was done. Based on the stone column’s deformation criteria and the soft clay bed’s settlement criteria, a comparison between the two was made.
Enhancing Subgrade Properties of Black Cotton Soil through the Combined Use of Sugarcane Bagasse Ash and Ceramic Waste Powder
Authors: Gouda Jagdish , Santosh B. , Sitarami Reddy D. , Vijay Kakade B. 
Published: June 2024

Abstract
This study explores the potential of Sugarcane Bagasse Ash (SBA) and Ceramic Waste Powder (CWP) in enhancing the poor black cotton (BC) soils, known for their swelling and shrinking tendencies due to high clay content. BC soils can compromise construction stability when exposed to moisture. The research involves mixing BC soil with varying proportions of SBA and CWP: 2.5% SBA and 5% CWP, 5% SBA and 10% CWP, 7.5% SBA and 15% CWP, and 10% SBA and 20% CWP. Laboratory tests show that higher SBA and CWP ratios reduce plasticity, free swell index, and Optimum Moisture Content (OMC) in the soil. This indicates that SBA and CWP additions mitigate soil plasticity and swelling. Moreover, parameters such as Maximum Dry Density (MDD), California Bearing Ratio (CBR), and unconfined compressive strength improve as SBA and CWP content increases, indicating enhanced soil strength. Laboratory findings support using up to 7.5% SBA and 15% CWP for effective subgrade soil stabilisation. A Plaxis 2D model confirms that these proportions significantly enhance pavement subgrade stability. In summary, this study demonstrates the positive impact of SBA and CWP on BC soils, reducing plasticity and swelling and improving soil strength. Using specific proportions of SBA and CWP effectively enhances subgrade soil stability, as verified by Plaxis 2D modelling.
Application of the HEC-HMS model to generate a flood hydrograph of an extreme event in a tropical basin
Authors: Babu Shruthi H , Sathish Kumar D 
Published: June 2024

Abstract
Hydrologic modeling using computer models has gained much attention in extreme flood event studies. Hydrologic Engineering Center Hydrologic Modelling System (HEC-HMS) is an extensively used software for streamflow generation in the hydrologic domain. This pilot study employs the HEC-HMS model in generating streamflows in the Chaliyar river basin, Kerala. Adequate representation of various water balance components of the hydrologic cycle is necessary for computing the surface and subsurface calculations. It is attained by combining appropriate sub-processes in the hydrological models. Remote sensing techniques integrated with Geographic Information Systems (GIS) are used in deriving the catchment characteristics. The simple canopy and surface methods are used to calculate the interception losses. The deficit-constant method is applied to estimate the infiltration losses, and the Clark unit hydrograph transforms the rainfall into runoff. The Muskingum method is used to route the reach segments within the watershed. Hydrometeorological data of the most influencing stations for the upstream Chaliyar basin are obtained by regionalization using the Thiessen polygon method. Daily precipitation data from four rain gauge stations, namely, Ambalavayal, Edakkara, Nilambur, and Manjeri, are used as the forcing inputs to the model. The streamflow data obtained from the Kuniyil gauge station is used to calibrate and validate the model. Various forecast skill scores like Probability of Detection (POD) and False Alarm Rate (FAR) are calculated from the categorical forecasts to quantify the forecast accuracy of the developed model. The model is used to simulate the intense flood event of 2019 in the Chaliyar basin.
Snow Cover Variability in the Beas River Basin and its relation with climate parameters during 2007-2018
Authors: Sunita  , Gupta Pardeep Kumar , Gusain Hemendra Singh , Gill Anhad Singh , Sidhu Onkar Singh 
Published: June 2024

Abstract
In the Himalayan zone, snow is a crucial component of cryosphere for efficient use of water resource management. The major objective of this research paper is to analyse snow dynamics in the Beas River basin using MODIS satellite images from 2007-2018, thus revealing important insights into the region’s snow cover variability and its potential impacts on the hydrological cycle. In this paper, the snow cover area (SCA) analysis has been done for the Beas River basin from 2007-2018 using the 8-day improved snow cover product (version 6) Terra-aqua (MOYDGL06*) MODIS sensor images and ERA5 data for winter period i.e., November to April. During the time period, SCA in the region ranged from ~46% (Nov 2016) to ~92% (Feb 2015). SCA and total precipitation were found to be declining at rates of 2.5 km2 and 52.2 cm, respectively. While the average temperature has been rising from 2007 to 2013 at a pace of 0.14°C. Though, SCA decreased at a faster rate of 20.49 km2 and total precipitation decreased at a faster rate of 36.2 cm during 2013-2018. In contrast, the mean temperature increased at a higher rate (0.38 °C). The study finds that SCA and precipitation are falling at a faster rate during 2013-2018. The trend derived from satellite data analysis of SCA was found to be consistent with the climate parameters. The study suggests that climate change is likely a major factor contributing to the observed trends in SCA, total precipitation, and mean temperature. The study also notes that the observed SCA trend is consistent with climate parameters. The paper investigates the fluctuations in SCA from November to April.
Waste materials as concrete aggregate - A systematic review
Authors: Banerjee Debargha , Nanda Radhikesh Prasad 
Published: June 2024

Abstract
Over the last few years, the rate at which metropolitan areas and industries have expanded worldwide has increased, leading to a significant increase in the usage of concrete and the depletion of natural resources like aggregate. This essay aims to thoroughly analyze the use of different wastes as aggregate in cement concrete. Critical reviews have been conducted on the consequences of using such waste materials on the mechanical characteristics of concrete products. From the results of many experiments, it may be inferred that waste can be used in cement concrete instead of natural aggregate. A thorough overview in tabular form is provided for quick access for the benefit of researchers. Further, the outcome of this investigation is expected to accelerate waste utilization for sustainable construction.
Microstructure and performance of carbon fiber reinforced aluminum matrix composites with molybdenum carbide coating on carbon fibers
Authors: Liu Tingting , He Xinbo , Zhang Lin , Ren Shubin , Qu Xuanhui 
Published: June 2024

Abstract
In this work, a molybdenum carbide coating on the surface of short carbon fibers prepared using molten salt method was proposed to ameliorate the interfacial bonding and improve the performance of carbon fiber/Al composites. The carbon fiber/Al composites were produced using vacuum hot pressing. The characteristics of molybdenum carbide coating were analyzed. Besides, the microstructures, bending strength and thermal properties of the carbon fiber/Al composites were explored. Furthermore, the interfacial thermal resistance of the composites was investigated in relation to theoretical evaluations derived from the combined Maxwell-Garnett effective medium approach and acoustic mismatch model schemes. The results indicated that a homogeneous Mo2C coating with a thickness of 0.5 μm was obtained by proper molar ratio of carbon fibers, MoO3 and chloride salts mixture and heated at 1000 °C for 60 min. The Mo2C coating greatly enhanced the bond between the aluminum matrix and carbon fiber, leading to improvements in the densification behavior and bending strength of the coated composites. The enhanced thermal properties including improved thermal conductivity and reduced coefficient of thermal expansion (CTE) were also achieved by the Mo2C coating. The in-plane thermal conductivity of 60 vol.% Mo2C-coated carbon fiber/Al composite was 221 W·m−1·K−1 enhanced by 92% compared to that of uncoated composite and the CTE was 6.0 × 10–6 K−1 which was suitable for electronic packaging materials.
Enhancing microstructural and mechanical properties of magnesium AZ31 matrix composites through friction stir processing incorporating silicon carbide, titanium carbide, and graphite particles
Authors: K P Boopathiraja , Ramamoorthi R , Hariprasad P , Arockiasamy Felix Sahayaraj 
Published: June 2024

Abstract
The present study focuses on investigating the effect of reinforcement on the microstructure and mechanical properties of friction-stir-processed magnesium hybrid composites. The groove width (0, 0.7, 1.1, 1.7, and 2.3 mm) of the Magnesium AZ31 plates was varied by varying the volume fractions (0, 5, 10, 15, and 20 vol%) of Silicon Carbide (SiC), Titanium Carbide (TiC), and Graphite (Gr) particle reinforcements in the hybrid composite. Single-pass processing was suspended using a cylindrical tool shoulder with a rotational speed, transverse velocity, and axial pressure of 1000 rpm, 30 mm min−1, and 6 kN, respectively. The optical micrograph clearly shows that a non-cluster zone (reinforcement particles are uniformly distributed without agglomeration) was identified in the processed region of the least concentrated composites. The results revealed that a peak tensile strength of 293.546 ± 5.12 MPa was attained for the combination of 10 vol% composites, and a Vickers hardness number of 86.53 HV was achieved for the 20 vol.% composites. The fracture surface morphology was analyzed using a Scanning Electron Microscope (SEM). The mode of tensile fractography was ductile for the least composite and transformed into a brittle mode of failure with the addition of reinforcements.
Flexible self-powered triboelectric nanogenerator sensor for wind speed measurement driven by moving trains
Authors: Dong Wentao , Huang Bo , Sheng Kaiqi , Cheng Xiao 
Published: June 2024

Abstract
Flexible self-powered sensors have been extensively applied to the Internet of Things, structural health monitoring (SHM), and intelligent transportation. It would be more demanding for the power supply to these sensors during the long-term maintenance of the rail transit system. The wind pressure/velocity generated by high-speed trains poses a substantial threat to safety of human, and new sensors without an external power supply should be developed to monitor wind pressure/velocity in the trackside. Flexible self-powered wind triboelectric nanogenerator (W-TENG) sensor with a single-electrode mode based on conductive hydrogel is designed to wind pressure/velocity monitoring without power supply by harvesting wind energy. It is devoted the relationship between the output voltage of the sensors and the wind pressure/velocity driven by high-speed trains. Material selection and structural design methods are adopted to enhance the energy harvesting efficiency and sensing accuracy of self-powered W-TENG sensors. Open-circuit current of 2.8 μA and open-circuit voltage of 12 V are achieved, and the output voltage signal has the linear relationship with trackside wind pressure/velocity. Field tests are implemented to evaluate the performance of self-powered W-TENG sensors in wind pressure/velocity measurement caused by moving trains, providing an idea to SHM application in intelligent transmit systems.
Examining the confluence of climate change and conflicts on agricultural and livestock exports in Somalia
Authors: Abdi Abdikafi Hassan , Mohamed Abdisalan Aden , Sugow Mohamed Okash , Halane Dhaqane Roble 
Published: June 2024

Abstract
Climate-induced extreme weather events and conflicts are jointly contributing to disruptions in agricultural supply chains and destabilizing global food trade. Since the literature has identified that variations in climatic conditions hamper farming and animal raising, it is necessary to explore the consequences of climate change on crop and livestock exports in order to implement policies that mitigate the exposure and enhance exports. In this context, this study aims to examine the confluence of climate change and conflicts—internal and external—on agricultural and livestock exports in Somalia during 1985–2017. The evidence from the cointegration analysis verified the presence of a consistent long-run cointegration between the variables. The empirical results of the ARDL approach indicate that average rainfall enhances agricultural and livestock exports in Somalia in the short-run and long-run, while mean temperature particularly hampers agricultural exports in the long-run. Despite livestock production was found to be statistically insignificant, crop production positively contributes to agricultural exports. In addition, increases in rural population enhance both export categories in the short-run and long-run. A striking finding from the study indicates that internal and external conflicts decrease crop and animal exports in the long-run, although the coefficients of external conflicts were statistically insignificant. The long-run findings were validated using the FMOLS cointegration approach. Moreover, the causality findings demonstrate a unidirectional causality from agricultural exports to precipitation, temperature fluctuations, and internal conflicts. Furthermore, the study shows that agricultural labor Granger causes farm and livestock exports. To this end, this study recommends policymakers promote product diversification, foster sustainable land management practices, facilitate market access, and invest in resilient farming systems.
Learning fast while changing slow in spiking neural networks
Authors: Capone Cristiano , Muratore Paolo 
Published: June 2024

Abstract
Reinforcement learning (RL) faces substantial challenges when applied to real-life problems, primarily stemming from the scarcity of available data due to limited interactions with the environment. This limitation is exacerbated by the fact that RL often demands a considerable volume of data for effective learning. The complexity escalates further when implementing RL in recurrent spiking networks, where inherent noise introduced by spikes adds a layer of difficulty. Life-long learning machines must inherently resolve the plasticity-stability paradox. Striking a balance between acquiring new knowledge and maintaining stability is crucial for artificial agents. To address this challenge, we draw inspiration from machine learning technology and introduce a biologically plausible implementation of proximal policy optimization, referred to as lf-cs (learning fast changing slow). Our approach results in two notable advancements: firstly, the capacity to assimilate new information into a new policy without requiring alterations to the current policy; and secondly, the capability to replay experiences without experiencing policy divergence. Furthermore, when contrasted with other experience replay techniques, our method demonstrates the added advantage of being computationally efficient in an online setting. We demonstrate that the proposed methodology enhances the efficiency of learning, showcasing its potential impact on neuromorphic and real-world applications.
Efficient sparse spiking auto-encoder for reconstruction, denoising and classification
Authors: Walters Ben , Rahimian Kalatehbali Hamid , Cai Zhengyu , Genov Roman , Amirsoleimani Amirali , Eshraghian Jason , Rahimi Azghadi Mostafa 
Published: June 2024

Abstract
Auto-encoders are capable of performing input reconstruction, denoising, and classification through an encoder-decoder structure. Spiking Auto-Encoders (SAEs) can utilize asynchronous sparse spikes to improve power efficiency and processing latency on neuromorphic hardware. In our work, we propose an efficient SAE trained using only Spike-Timing-Dependant Plasticity (STDP) learning. Our auto-encoder uses the Time-To-First-Spike (TTFS) encoding scheme and needs to update all synaptic weights only once per input, promoting both training and inference efficiency due to the extreme sparsity. We showcase robust reconstruction performance on the Modified National Institute of Standards and Technology (MNIST) and Fashion-MNIST datasets with significantly fewer spikes compared to state-of-the-art SAEs by 1–3 orders of magnitude. Moreover, we achieve robust noise reduction results on the MNIST dataset. When the same noisy inputs are used for classification, accuracy degradation is reduced by 30%–80% compared to prior works. It also exhibits classification accuracies comparable to previous STDP-based classifiers, while remaining competitive with other backpropagation-based spiking classifiers that require global learning through gradients and significantly more spikes for encoding and classification of MNIST/Fashion-MNIST inputs. The presented results demonstrate a promising pathway towards building efficient sparse spiking auto-encoders with local learning, making them highly suited for hardware integration.