Superior Technology Research Articles

Biocatalytic conversion of syngas to liquid biofuels using Clostridium acetobutylicum

This study aimed to develop a pilot-scale bioreactor for ethanol production from syngas produced from biomass gasification and evaluate its performance. Gasification of characterized feedstock, namely Casuarina wood and coconut shell, is performed in a 2 kg hr-1 downdraft gasifier and the produced gas is cooled in a heat exchanger and scrubbed in a scrubbing bed to produce syngas free of moisture, tar and particulates. The syngas are fermented to produce biofuels in a 5 L capacity bioreactor with Clostridium acetobutylicum strains. The percentage yield of acetone, butanol and ethanol was verified with the standard concentration and found to be 12%, 5% and 7% from casuarina wood and 13%, 7% and 6% from coconut shell respectively. The syngas components viz., carbon monoxide (CO), carbon dioxide (CO2) and hydrogen (H), are fermented to produce acetone, butanol and ethanol along with larger proportions of acids. These acids can be converted into bio-alcohol if the fermentation period or gas-liquid transfer is enhanced. The pretreatment of feedstock is not required in syngas fermentation as it is a major process in conventional bio-alcohol production methods. This pays a way to superior technology in terms of cost and time.

A Data-Driven Algorithm for Dynamic Parameter Estimation of an Alkaline Electrolysis System Combining Online Reinforcement Learning and k-Means Clustering Analysis

Determining the electrochemical, thermal, and mass transfer dynamics embedded in an alkaline electrolysis (AEL) system provides important information about the application of ancillary services provided by hydrogen energy for the elimination of carbon emissions. Therefore, there is an urgent need to develop methodologies for evaluating key parameters, such as overvoltage coefficients, stack transfer capacity, diaphragm thickness, and permeability, to accurately capture the system’s fluctuating characteristics. However, limited by the lack of superior sensor technology, some significant variables cannot be measured directly. In this context, comprehensively accurate parameters of an estimation strategy offer a novel alternative to characterize the system’s corresponding intrinsic nature. This paper was motivated by this arduous challenge and aims to address the large branching factors with irregular properties. Specifically, the associated mathematical models reflecting the transient operating parameters in terms of electrochemical, heat transfer, and mass transfer are first established. Subsequently, k-means clustering analysis is conducted to deduce the similarity of distribution of the measured variables, which can function as proxies of the separator to distinguish the working status. Furthermore, online reinforcement learning (RL), renowned for its ability to operate without extensive predefined datasets, is employed to conduct dynamic parameter estimation, thereby approximating the robust nonlinear and stochastic behaviors within AEL components. Finally, the experimental results verify that the proposed model achieves significant improvements in estimation errors compared to existing parameter estimation methods (such as EKF and UKF). The enhancements are 76.7%, 54.96%, 51.84%, and 31% in terms of RMSE, NRMSE, PCC, and MPE, respectively.

Novel Cu-MXene hybrid nanofluids for the experimental investigation of thermal performance in double pipe heat exchanger

This work aims at analyzing the performance of a double-pipe heat exchanger (DPHE) using low concentrated (0.02–0.06 vol%) water, methanol, castor oil and silicon oil based Cu-MXene hybrid nanofluids. Convective heat transfer experiments were successfully performed in fabricated modular double pipe heat exchanger without using any twisted tapes, surfaces and effectively measured various heat transfer parameters such as Nusselt number (Nu), heat transfer coefficient (h), rate of heat transfer (Q), overall heat transfer coefficient (U), friction factor (f), pressure drop (∆P), and the thermal performance factor (TPF). The results indicated a considerable improvement in Nu, h, and U with some penalty in ∆P. Moreover, the TPF value of methanol and water-based hybrid nanofluids exceeded unity and showed superior heat transfer characteristics, confirming the viability of improving thermal performance in DPHE. Eventually, the LMTD and U of hybrid nanofluids were positively validated using Aspen HYSYS 12.1 version software to verify the experimental results and showed a variation of less than ± 5.35% for U and LMTD. These results successfully demonstrate the possible usage of proposed Cu-MXene hybrid nanofluids in thermal management systems, automotive cooling, and industrial cooling respectively. In addition, these findings also encourage its use in superior performance and cost-effective thermal management technologies.

Clinical Validation of a Targeted RNA-Sequencing Assay for Driver Gene Alteration Detection in Non-Small Cell Lung Cancer.

With the increasing number of diagnostic biomarkers associated with tumor diagnosis, targeted therapy, and immunotherapy, access to clinical pathological specimens of anappropriate size for analysis is becoming a problem. Conventional high-throughput sequencing assays for non-small cell lung cancer (NSCLC) often necessitate the extraction of separate DNA and RNA samples to achieve precise detection of various mutation types. This study aimed to employ RNA-next-generation sequencing (NGS) technology to simultaneously detect different types of mutations in NSCLC samples, including single nucleotide variations, insertions and deletions, fusions/rearrangements, and exon skipping, thereby addressing the issue of limited sample availability. Two hundred and twenty cases of formalin-fixed paraffin-embedded NSCLC clinical specimens were retrospectively included for targeted RNA sequencing based on the principle of probe hybridization capture. Lung cancer tissue samples with different storage times were compared for success in DNA-NGS and RNA-NGS assays. The clinical detection performance of RNA-NGS was evaluated by comparing its results to those of DNA-NGS and clinical assays. Samples with inconsistent results were further verified by immunohistochemistry, amplification refractory mutation system-polymerase chain reaction, or droplet digital polymerase chain reaction. DNA-NGS exhibited an overall success rate of 91.82% in all samples, while RNA-NGS achieved an overall success rate of 92.73%. However, the success rate declined with longer storage times. Compared with DNA-NGS, targeted RNA sequencing for single nucleotide variation/insertion and deletion detection achieved a sensitivity of 93.75%, a specificity of 100%, and an overall concordance of 97.86%. Compared with the validated results, it achieved a sensitivity of 97.96%, a specificity of 99.28%, an and overall concordance of 98.93% in fusion/rearrangement and Met exon skipping detection, which was superior to DNA-NGS. Compared to clinical testing, this assay demonstrated a sensitivity of 93.33%, a specificity of 100%, and an overall concordance rate of 97.93%. This study substantiates that the targeted RNA-sequencing assay, based on probe hybridization capture, represents a superior detection technology platform for the application of drug targeting. It expeditiously and reliably provides all the requisite biomarkers for current NSCLC targeted therapies in a single-sample testing workflow, facilitating rapid clinical diagnosis and the formulation of rational treatment plans by clinicians.

A Model of Charles Ponzi

We develop a model of Ponzi schemes with asymmetric information to study Ponzi frauds. A long-lived agent offers to save on behalf of short-lived agents at a higher rate than they can earn themselves. The long-lived agent may genuinely have a superior savings technology, but may be an imposter trying to steal from short-lived agents. The model identifies when a Ponzi fraud can occur and what interventions can prevent it. A key feature of Ponzi frauds is that the long-lived agent builds trust over time and improves their reputation by keeping the scheme going.

BIOREMEDIATION: A SUPERIOR ALTERNATIVE FOR REMEDIATING TANNERY EFFLUENT-CONTAMINATED SOIL

Tannery effluent poses significant risks to soil health, primarily through contamination with heavy metals like chromium, sulphides, and persistent organic pollutants (POPs). These toxic substances inhibit microbial activity, reducing nutrient cycling and organic matter decomposition essential for soil fertility. Beneficial microorganisms, including nitrogen-fixing bacteria, are particularly affected, leading to altered microbial communities dominated by less advantageous, metal-tolerant species. Accumulation of POPs and heavy metals disrupts soil enzymatic activities, interferes with plant root growth, and complicates remediation efforts due to pollutant migration to groundwater and potential entry into the food chain. Prolonged exposure to such contaminants diminishes soil fertility, reduces resilience, and disrupts ecosystem services, posing threats to agricultural productivity and environmental health. This review was aimed to outline what made bioremediation a superior treatment technology among other methods used in remediating tannery effluent contaminated soil. Efforts to mitigate tannery effluent impacts involve a combination of physical, chemical, and biological remediation technologies. Physical methods like soil washing, flushing, and thermal desorption focus on removing or isolating contaminants, while chemical approaches such as oxidation, reduction, and stabilization transform pollutants to less harmful forms or immobilize them. Biological remediation leverages microorganisms and plants to detoxify contaminants sustainably. Bioremediation strategies with aid of bioaugmentation and biostimulation do enhance microbial activity to address organic and inorganic pollutants effectively more than physical and chemical methods. Another excellent bioremediation technology called phytoremediation can also address organic and inorganic pollutants effectively, Achieving better remediation technique should be coupled with stringent industrial regulations, sustainable tanning methods, and stakeholder awareness

Survival Strategies For Rice Farmers On Roductivity In Tanjung Beringin Village West Tabir Subdistrict

This research was motivated by the existence of an imbalance in rice productivity in Tanjung Beringin Village for the last five years from 2018-2022, where in 2022, there was a relatively low decline in rice productivity from the previous year. This problem shows that there are major challenges faced by rice farmers in Tanjung Beringin Village in terms of climate change, resource availability, and agricultural practices that have been carried out, so that rice farmers in Tanjung Beringin Village apply survival strategies so that rice productivity increases. Thus this study aims to analyze the survival strategy for rice farmers in productivity in Tanjung Beringin Village, West Tabir District. The theory used is the theory of survival strategies from Hardestry (1977). This research uses a descriptive qualitative approach, with data collection techniques through observation, interviews, and documentation. The data analysis used the interactive method of Miles and Huberman. The results of this study indicate that the strategy of rice farmers in Tanjung Beringin Village in maintaining productivity implements strategies: 1) Technology adaptation with the use of superior rice varieties and water management technology in the form of making small ponds or intermittent irrigation. 2) Socio-economic capacity building through strengthening cooperation between farmers, diversification of farming businesses, and utilization of local labor, 3) Environmental risk management strategies by using organic fertilizers, and conservative soil management.

Bionic Recognition Technologies Inspired by Biological Mechanosensory Systems.

Mechanical information is a medium for perceptual interaction and health monitoring of organisms or intelligent mechanical equipment, including force, vibration, sound, and flow. Researchers are increasingly deploying mechanical information recognition technologies (MIRT) that integrate information acquisition, pre-processing, and processing functions and are expected to enable advanced applications. However, this also poses significant challenges to information acquisition performance and information processing efficiency. The novel and exciting mechanosensory systems of organisms in nature have inspired us to develop superior mechanical information bionic recognition technologies (MIBRT) based on novel bionic materials, structures, and devices to address these challenges. Herein, first bionic strategies for information pre-processing are presented and their importance for high-performance information acquisition is highlighted. Subsequently, design strategies and considerations for high-performance sensors inspired by mechanoreceptors of organisms are described. Then, the design concepts of the neuromorphic devices are summarized in order to replicate the information processing functions of a biological nervous system. Additionally, the ability of MIBRT is investigated to recognize basic mechanical information. Furthermore, further potential applications of MIBRT in intelligent robots, healthcare, and virtual reality are explored with a view to solve a range of complex tasks. Finally, potential future challenges and opportunities for MIBRT are identified from multiple perspectives.

Evaluation of Technical Aspects of Solar Photovoltaic (PV) Power Installations on Farmland

This research evaluates the technical and economic aspects of solar photovoltaic (PV) power installations on farmland, utilizing a simulation model in MATLAB to forecast annual system output based on nominal power and meteorological data. This study compares various configurations, including single-sided versus double-sided modules and fixed versus tracker structures, to determine their efficiency, losses, and economic viability. The findings indicate that, while theoretically superior technologies may offer better production rates, their economic feasibility varies significantly depending on specific project conditions. The main conclusions drawn from this research emphasize that land-based PV systems present a promising solution for sustainable energy generation. By addressing challenges such as solar energy intermittency and the need for supportive infrastructure, this study highlights the potential for these systems to significantly contribute to reducing greenhouse gas emissions and enhancing energy resilience. This analysis underscores the importance of optimizing configurations to maximize both technical performance and economic returns, ultimately supporting a transition towards a more sustainable energy future.

Logistics of British counterinsurgency during the Indian Rebellion: 1857–1859

ABSTRACT In the summer of 1857, the Bengal Army mutinied against the East India Company (EIC). Simultaneously, a civil rebellion erupted in north India. The Indian civil and military mutineers are clubbed together as rebels. The rebels conducted battles, sieges, and guerrilla warfare against the EIC. This article focuses on the logistics of British counterinsurgency between 1857 and 1859. The British won the “battle of logistics” because they had the resources of a global maritime state and superior industrial technology. Besides greater financial and technological resources, managerial innovations and use of Indian resources gave the British victory over the rebels.

The Influence Of Cultural, Social And Personal Factors On The Interest In Purchase Intention Non-Subsidized Fertilizer At Toko UD. Sejahtera Bersama In Kecamatan Bahorok

Fertilizer is a substance or material that is used in plants to improve physical, chemical, or biological characteristics in order to increase the availability of nutrients, which results in an increase in plant growth. There are two types of fertilizer in Indonesia: subsidies and non-subsidized. While subsidies are provided by the government, non-subsidized are those that are provided outside of government programs and do not qualify for subsidies. Non-subsidized fertilizers, although they have superior quality and technology compared to subsidized fertilizers, still face problems in terms of farmers' Purchase Intention, especially in Kecamatan Bahorok. The purpose of this study is to examine the effects of cultural, social, and private factors on the desire to purchase intention non-subsidized fertilizer at Toko UD. Sejahtera Bersama in Kecamatan Bahorok. Data collection using a questionnaire given to 90 respondents. The model used is multiple linear regression and is processed using SPSS. The results of this study indicate that cultural factors partially do not have a positive and significant influence, social factors partially do not have a positive and significant influence and personal factors partially have a positive and significant influence. The Adjusted R Square value of 0.541 means that Purchase Intention can be explained by cultural, social and personal factors by 52.5% and the remaining 47.5% can be explained by other variables not studied.

Optimizing QoS in Wireless Sensor Networks: A Review of Advanced Traffic Control Protocols and Techniques

In wireless sensor network technology (WSNs) the proper congestion processing is the essential key to prevent the parameters of QoS from facing intense loss such as Likelihood of occurrence output reduction and also it may lead to maximize the consumed energy and it also reflect on the increase of the end-to-end time delivery side by side with a noticeable decrease in the percentage of transmitted packet arrival at the destination end. Thus, evolving more superior technology is consider to be one of the most significant challenge in (WSNs) that help to deal with issues like avidness, detection and control in WSNs. This paper review most updated protocols to mitigate the dilemmas of congestion in the WSNs based on the mechanism of congestion’s innate behavior. The protocol categories can be divided into three divisions which are traffic based, resource based and hybrid. The first protocol category (traffic-based) is also witnessed more subdivide based on either the techniques of end-to-end transmission or hop-by-hop. Both the establishment procedure of route and the exploit of active bandwidth techniques. It is also important to indicate that inner operational process of the attenuation linked to congestion protocols are discuss in this paper. Lastly. An intensive study is exploited in this paper to analyze congestion protocols in connection with different performance standards in order to determine which a specific protocol category case is worth to develop. The performance survey shows that the difficulties of accurate detection to the congestion for a particular network if it is only considering the protocols class attitude when it alters with applicable platform and a metric on its own.

Identification of Inpari HDB 32 Superior Rice Seeds based on Android in Realtime with Artificial Neural Network

Rice is a staple food for humans living in East Asia. Rice is a crystal fruit. The Latin name for rice is Oryza Sativa. Rice plants are 110-120 days old. The selection of quality rice seeds by farmers is seen from the bright yellow color of the rice without black/brown spots, its large size and rounder. Rice seeds that are not of good quality are dark brown in color, have black/brown spots, and are flat in shape. The absence of superior rice recognition technology that is not Android-based in real time is the main reason for this research. The focus of this research is to identify superior and non-superior rice in Inpari HDB 32 rice with a high recognition accuracy rate of more than 70 percent with a viewing angle of 0-180 degrees using the real-time ANN method. The training data used in this research was 1000 datasets consisting of 350 superior rice datasets and 650 non-superior datasets. The smart model for classifying rice seeds that has been built in this research is generally able to run well where the classification accuracy obtained is quite good. The classification accuracy of the ANN model during training of the neural network model was able to classify rice seeds with an accuracy of 70-100% with the confidence value of the real-time classification results ranging from 65-98%. Real-time classification of rice grains with maximum accuracy of 96% and many grains 73%.

Peran Kompetensi Soft Skills Digital Native dalam Meraih Kesuksesan dalam Berkarir di Dunia Kerja

The digital era has created a generation of digital natives with superior technology adaptability. However, to achieve success in the world of work, soft skills competencies remain an important factor that supports individual success. This study aims to explore the role of soft skills competencies in digital natives in building a successful career. Using a qualitative approach, data was collected through in-depth interviews with young digital native workers in various industry sectors. The results showed that interpersonal communication skills, teamwork, adaptability, and time management were the main elements that contributed to their success. The findings highlight the importance of synergy between technical and soft skills in facing the complex challenges of the world of work. The implications of this study offer insights for organizations to develop training programs that are holistic and support the development of soft skills as part of a human capital capacity building strategy.

The Integration of Large Language Models in Financial Services: From Fraud Detection to Generative AI Applications

This comprehensive article examines the transformative impact of artificial intelligence in the financial services sector, focusing on the evolution from traditional applications to advanced AI systems. Through systematic analysis of implementation frameworks and regulatory considerations, this article demonstrates the sector's technological leadership, evidenced by a 56% higher AI implementation success rate compared to other industries. The article reveals how Large Language Models have revolutionized customer interactions, achieving 92% query resolution accuracy and 89% improvement in user engagement. Documentation and compliance processes have been transformed through AI automation, demonstrating an 82% improvement in real-time compliance monitoring and 89% enhancement in automated reporting accuracy. Financial institutions' established regulatory frameworks and mature governance structures have enabled superior technology integration, with an 82% cloud adoption rate and 85% risk management effectiveness. The article’s analysis of software development infrastructure shows significant advancement, with a 73% improvement in deployment frequency and 82% enhancement in code quality metrics. The article highlights how financial institutions' robust regulatory expertise provides a significant competitive advantage, demonstrated by 89% security compliance and 76% stronger compliance protocols. Drawing from comprehensive industry analyses and empirical evidence, this article contributes to the growing body of literature on AI implementation in regulated industries while providing practical insights for organizations balancing innovation with compliance requirements.

Gazing at long-term linkages between agricultural land use and population growth in India: an inverted “U-shape” relationship

Abstract This study investigates the linkages between changes in agricultural land use and population growth in India. We have employed long-term time series and a panel dataset of 1869 samples (267 districts × 7 time points from 1961 to 2021) to determine this. We theorize that there is an inverted “U-shape” relationship between changes in population growth and agricultural land. Our findings suggest a positive impact of population growth on the change in cultivated land. However, this relationship was not static during 1961–2021. We found a two-stage split relationship with a breakpoint in 1981. Prior to the 1980s, there was a 12% expansion in cultivated land in response to a unit increase in population growth. During the post-1980s, with a unit decline in population growth, there was a 5% reduction in cultivated land. The findings were reaffirmed through several robustness checks: analyses using alternative outcome variables, alternative break points in a segmented regression model, and spatial modeling. From a policy perspective, this study advances the need for the reduction of population growth rate in high-fertility states and the adoption of superior and green technology for agricultural intensification and diversification to stop cropland expansion at the cost of environmental sustainability.

Evaluating deuterated-xylene for use as a fusion neutron spectrometer.

The spectrum of neutrons emitted by thermonuclear plasmas encodes information about the fuel ion distribution function. Measuring these fast neutron spectra with sufficient resolution allows for the measurement of plasma properties such as the ion temperature and strength and energy of fast ion populations. Liquid organic scintillators are a commonly used fast neutron detection technology because of their high detection efficiency and ability to discriminate between neutrons and gammas. However, performing detailed spectroscopy with these detectors is difficult because of the isotropic nature of neutron scattering on protons, the dominant mechanism of interaction. Deuterium-based scintillators have shown promise as a superior spectrometer technology because of the anisotropic nature of neutron scattering on deuterium, which significantly improves the condition number of the detector response matrix [Lawrence et al., Nucl. Instrum. Methods Phys. Res., Sect. A 729, 924 (2013)]. Deuterated-xylene, now available commercially, has advantages in light output and safety over benzene-based deuterated scintillators [Becchetti et al., Nucl. Instrum. Methods Phys. Res., Sect. A 820, 112 (2016)]. We present experimental spectrum unfoldings made by 2 in. right cylindrical protiated-xylene and deuterated-xylene detectors with response matrices generated with Geant4 and additional data from the literature. We compare their performance by measuring the neutron spectrum produced by an AmBe source and deuterium-tritium (DT) neutron generators. We find that the deuterated scintillator outperforms the protiated one for AmBe and DT spectra, suggesting deuterated-xylene should be considered for future fusion neutron spectrometry applications.

Highly efficient cyan-emitting glass-ceramic with superior thermal stability: A solution to the cyan gap in full-spectrum W-LED lighting

Highly efficient cyan-emitting glass-ceramic with superior thermal stability: A solution to the cyan gap in full-spectrum W-LED lighting

Pengembangan Teknologi Metaverse Ekosistem E-Mobility Pada Pameran Teknologi International Berbasis Augmented Reality

Augmented Reality (AR) can be used as a new technology in organizing virtual and paperless exhibitions to make the products on display more attractive and updated regularly. This can happen because AR is a technology that integrates the virtual and real worlds. AR has been widely used as a medium to assist in providing information in real-time in an interesting, interactive, and educational way. This journal explains the development of AR media and its feasibility as an international promotional media in introducing the E-Mobility Ecosystem. The E-Mobility Ecosystem is a PENTA-branded convertible electric car, one of PNJ's superior technologies. The Hannover Messe'23 exhibition with the theme "Making Indonesia 4.0" requires products to be displayed in digital form (paperless). Thus, an application is needed to support digital promotion. This research aims to develop a Marker-Based AR application as one of the promotional media for E-Mobility Ecosystem products, which consist of charging stations, electric vehicles, and the Center Of Otomo-tive. The output of this research is an application that can show E-Mobility Ecosystem products by displaying a 3D Model when the mobile camera is directed at a card given an Object marker. This research method uses the Multimedia Development Life Cycle (MDLC). This research has been successfully developed and distributed. This is evidenced by user assessment using a Likert scale with a success rate of 87.8% strongly agree.

Comparative analysis and directed protein evolution yield an improved degron technology with minimal basal degradation, rapid inducible depletion, and faster recovery of target proteins.

Biological mechanisms are inherently dynamic, requiring precise and rapid gene manipulation for effective characterization. Traditional genetic perturbation tools such as siRNA and CRISPR knockout operate on timescales that render them unsuitable for exploring dynamic processes or studying essential genes, where chronic depletion can lead to cell death. Here, we compared four major inducible degron systems-dTAG, HaloPROTAC, and two auxin-inducible degron (AID) tools-in human pluripotent stem cells. We evaluated basal degradation levels, inducible degradation kinetics, and recovery dynamics for endogenously tagged genes. While the AID 2.0 system is the most efficient for rapid protein degradation, it exhibited higher basal degradation and slower recovery after ligand washout. To address these challenges, we applied directed protein evolution, incorporating base-editing-mediated mutagenesis and iterative functional selection and screening. We discovered novel OsTIR1 variants, including S210A, with significantly enhanced overall degron efficiency. The resulting system, designated as AID 3.0, demonstrates minimal basal degradation and rapid and effective target protein depletion and substantially rescues the cellular and molecular phenotypes due to basal degradation or slow target protein recovery in previous systems. We conclude that AID 3.0 represents a superior degron technology, offering a valuable tool for studying gene functions in dynamic biological contexts and exploring therapeutic applications. Additionally, the research strategy used here could be broadly applicable for improving other degron and biological tools.