Reliable Technology Research Articles

Interactive Technologies in Online Teacher Education in Africa: A Systematic Review 2014–2024

This systematic review investigates the integration of interactive technologies in online teacher education across Africa from 2014 to 2024. The study aims to identify the types of interactive technologies employed, the leading countries in regard to their adoption, and the outcomes of their usage on teacher training programs. Despite significant advancements, particularly in countries like Kenya and South Africa, the effectiveness of these technologies varies widely due to infrastructural, socio-economic, and policy-related challenges. The findings highlight the critical role of reliable information communication technology (ICT) infrastructure, culturally relevant content, and comprehensive training for educators in optimizing the use of interactive technologies. Additionally, the study emphasizes the need for greater policy coordination and collaboration among African nations to fully leverage these technologies. The review concludes that, while interactive technologies hold substantial potential in terms of transforming teacher education in Africa, sustained efforts are required to overcome the existing barriers and ensure equitable access to quality education across the continent.

Computational Exploration of Adsorption-Based Hydrogen Storage in Mg-Alkoxide Functionalized Covalent-Organic Frameworks (COFs): Force-Field and Machine Learning Models.

Hydrogen is a clean-burning fuel that can be converted to other forms. of energy without generating any greenhouse gases. Currently, hydrogen is stored either by compression to high pressure (>700 bar) or cryogenic cooling to liquid form (<23 K). Therefore, it is essential to develop safe, reliable, and energy-efficient storage technology that can store hydrogen at lower pressures and temperatures. In this work, we systematically designed 2902 Mg-alkoxide-functionalized covalent-organic frameworks (COFs) and performed high-throughput (HT) computational screening for hydrogen storage applications at 111, 231, and 296 K. To accurately model the interaction between Mg-alkoxide sites and molecular hydrogen, we performed MP2 calculations to compute the hydrogen binding energy for different types of functionalized models, and the data were subsequently used to fit modified-Morse force field (FF) parameters. Using the developed FF models, we conducted HT grand canonical Monte Carlo (GCMC) simulations to compute hydrogen uptakes for both original and functionalized COFs. The generated data were subsequently used to evaluate the materials' gravimetric and volumetric storage performance at various temperatures (111, 231, and 296 K). Finally, we developed machine learning (ML) models to predict the hydrogen storage performance of functionalized structures based on the features of the original structures. The developed model showed excellent performance with a mean absolute error (MAE) of 0.061 wt % and 0.456 g/L for predicting the gravimetric and volumetric deliverable capacities, enabling a quick evaluation of structures in a hypothetical COF database. The screening results demonstrated that the Mg-alkoxide functionalization yields greater improvements in volumetric H2 storage capacities for COFs with smaller pores compared to those with larger (mesoporous) pores.

Results on the Use of an Original Burner for Reducing the Three-Way Catalyst Light-Off Time

Individual road mobility comes with two major challenges: greenhouse gas emissions related to global warming and chemical pollution. For the pollution reduction in the spark ignition engine vehicle, the standard and reliable aftertreatment technology is the three-way catalytic converter (TWC). However, the TWC starts to convert once an optimal temperature, usually known as the light-off temperature, is reached. There are many methods to reduce the warm-up period of the TWC, among which is using a burner. The initial question underlying this study was to see if the use of a relatively straightforward extra-combustion device mounted upstream the TWC, without complex elements, was able to serve the purpose of reducing the light-off time. Consequently, an original burner was designed and investigated numerically via the CFD method and experimentally via measurements of the temperature evolution within a TWC, along with the emissions specific to the burner’s operation. The main findings of this study are: (1) the CFD-based examination is a good way to decide on how to achieve the so-called fit-for-purpose internal aerodynamics of the burner (i.e., to obtain a homogeneous mixture) and (2) to reach the light-off temperature, conventionally taken as 500 K, the burner was operated for 5.2 s, i.e., 3.6 g of gasoline injected, 2.7 g of CO2 and 1.351 g of CO, respectively, emitted. Moreover, this study identified measures for improving the burner’s design as well as an enhanced procedure for the burner’s operating control both aiming to produce a cleaner combustion during the TWC pre-heating.

Test-retest reliability and construct validity of Inosen’s Silat Momentum Test

Problem Statements: The kick in Pencak Silat has a magnitude called momentum, which requires a tool capable of measuring several variables based on the International System of Units (SI) in real-time. Nowadays, there are affordable and reliable sensor technologies to meet these needs. Purpose: The research aimed to design a test instrument that utilizes sensor technology to measure kick momentum in the sparring category of Pencak Silat following the applicable SI, and to test its reliability and validity. The resulting instrument is named Inosen’s Silat Momentum Test. Approach: This study followed Johnson and Nelson’s seven-test construction process. Twenty-four Pencak Silat athletes, consisting of 12 elite and 12 non-elite participants, were involved in the evaluation process. The test’s reliability was assessed by examining the correlation between the test and retest results. The construct validity test was conducted by comparing the results of the front kick tests of elite and non-elite Pencak Silat athletes. Data analysis was performed using Pearson correlation and independent t-tests using Minitab 21.4.1 software. Results: The results of the test and retest indicate a very high correlation (r = 0.923), demonstrating the consistent ability of Inosen’s Silat Momentum Test to measure kick momentum. The study found a statistically significant difference in the Inosen’s Silat Momentum Test scores (p &lt; 0.05) between the elite fighter group (average score of 463.3 kg.m/s) and the non-elite fighter group (average score of 375 kg.m/s). The results indicate that Inosen’s Silat Momentum Test is an effective instrument for differentiating kick momentum based on fighter performance. Conclusions: Based on the findings, it is inferred that Inosen’s Silat Momentum Test is a reliable and valid instrument for measuring Pencak Silat kick momentum according to SI standards. Keywords: biomechanics, kick momentum, pencak silat, performance test, sensor technology.

Enhanced detection of glyphosate with a Co-MOF integrated opto-electrochemical sensor

Abstract This study presents a new method for detecting the organophosphorus pesticide glyphosate using advanced scanning electrodes (SPE) and enhanced fluorescence. Metal-organic frameworks from cobalt ions were synthesized using a solvothermal method. It is characterized using Raman spectroscopy, FT-IR, and X-ray diffraction techniques. The electrocatalytic behavior of the materials was studied using electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV). Differential pulse voltammetry (DPV) examined the positive response of plants to glyphosate over a concentration range of 0.55–5.95 mM with a detection limit of 0.334 mM. The fluorescence enhancement ranges from 0.07 mM to 0.67 mM, and the detection limit is 0.0998 mM. Additionally, the selectivity of the proposed opto-electrochemical sensor was evaluated. This selection demonstrates the sensor's ability to detect glyphosate in complex wastewater matrices. This has important implications for environmental monitoring. By addressing glyphosate contamination, the sensor could significantly advance ecological remediation and monitoring strategies. The selectivity, sensitivity, and ability to operate under harsh conditions represent a significant advance in the development of efficient and reliable glyphosate technology for wastewater treatment and environmental protection. In real-sample matrices, the suggested sensor showed a good recovery of the pesticide that had been spiked.

Efficacy of Phthalocyanine‐Based Catalysts in Electrochemical Sensors: A Comprehensive Review

AbstractMetal phthalocyanines (MPcs) are promising materials for electrochemical sensing due to their physicochemical properties, including redox activity, structural versatility, and chemical stability. These materials can incorporate various metals into their central core, ensuring tunable catalytic activity and enhanced sensitivity and selectivity. This makes MPcs valuable for designing advanced electrochemical sensors, which require precise and reliable performance for applications ranging from environmental monitoring to biomedical diagnostics. This review discusses the advancements in MPc‐based catalysts for electrochemical sensors, focusing on their superior catalytic properties, stability under diverse operating conditions, and high functionalization potential. The unique redox behavior of the metal center in MPcs ensures improved detection capabilities of analytes like biomolecules, heavy metal ions, and environmental pollutants, positioning MPc materials as a cornerstone in future sensor technology. MPc‐based sensors have diverse applications across various fields, including environmental sensing, medical diagnostics, and industrial process monitoring. Recent reports highlight the practical relevance and growing importance of MPcs in real‐world applications. Challenges associated with MPc‐based sensors include scalability, environmental stability, and integration into practical devices. The review concludes with a discussion on the future outlook on MPcs in the design and development of next‐generation electrochemical sensors, paving the way for more efficient, cost‐effective, and reliable detection technologies.

Perspectives on Anesthesia and Perioperative Patient Safety: Past, Present, and Future.

During the past 70 years, patient safety science has evolved through four organizational frameworks known as Safety-0, Safety -1, Safety-2, and Safety-3. Their evolution reflects the realization over time that blaming people, chasing errors, fixing one-offs, and regulation would not create the desired patient safety. In Safety-0, the oldest framework, harm events arise from clinician failure; event prevention relies on better staffing, education, and basic standards. In Safety-1, used by hospitals, harm events arise from individual and/or system failures. Safety is improved through analytics, workplace culture, high reliability principles, technology, and quality improvement. Safety-2 emphasizes clinicians' adaptability to prevent harm events in an everchanging environment, using resilience engineering principles. Safety-3, used by aviation, adds system design and control elements to Safety-1 and Safety-2, deploying human factors, design-thinking, and operational control or feedback to prevent and respond to harm events. Safety-3 represents a potential way for anesthesia and perioperative care to become safer.

Design of Underwater Cables Applicable to Submarine(KSS-III Batch-II) Navigation Radar

Since the creation of the first submarine telegraph cable connecting England and France in 1850, today, due to the rapid development of the Internet and Communications fields, the demand for submarine communication cables has increased and continues to develop. Submarine cables are designed and manufactured to be suitable for the maritime environment, and many parts are imported from overseas, and several domestic cable manufacturers are producing them for commercial purposes. Field-proven and reliable commercial submarine communication cable technology is also being applied to the military field, and is especially actively utilized in naval surface ships and submarines. This paper is about the design of an underwater cable applicable to submarine(KSS-III Bach-II) navigation radar and also is to secure the performance of an underwater cable with bending durability in extreme marine environments, emergency diving, and repeated mast raising and lowering. Finally, we hop that the domestic development of underwater cables will help improve the performance of navigation radars for submarines.

Impact of Audio-Visual Complexity on Symptomatology of Laryngeal Dystonia: A Virtual Reality Study.

Laryngeal dystonia (LD) is an isolated focal dystonia characterized by involuntary spasms in laryngeal muscles selectively impairing speech production. Anecdotal observations reported the worsening of LD symptoms in stressful or vocally demanding situations. To examine the impact of surrounding audio-visual complexity on LD symptomatology for a better understanding of disorder phenomenology. We developed well-controlled virtual reality (VR) environments of real-life interpersonal communications to investigate how different levels of audio-visual complexity may impact LD symptoms. The VR experiments were conducted over five consecutive days, during which each patient experienced 10 h of 4100 experimental trials in VR with gradually increasing audio-visual complexity. Daily reports were collected about patients' voice changes, as well as their comfort, engagement, concentration, and drowsiness from using VR technology. After a weekly VR exposure, 82% of patients reported changes in their voice symptoms related to changes in background audio-visual complexity. Significant differences in voice symptoms were found between the first two levels of the audio-visual challenge complexity independent of study sessions or VR environments. This study demonstrated that LD symptoms are impacted by audio-visual background across various virtual realistic settings. These findings should be taken into consideration when planning behavioral experiments or evaluating the outcomes of clinical trials in these patients. Moreover, these data show that VR presents a reliable and useful technology for providing real-life assessments of the impact of various experimental settings, such as during the testing of novel therapeutic interventions in these patients. Level 3 Laryngoscope, 2024.

Reliability analysis of subsea manifold system using FMECA and FFTA

Subsea manifold system is a complex system that occupies a pivotal role in contemporary ocean engineering and has a significant impact on the safety of marine resource exploitation. Reliability technology plays a significant role in ensuring the safe operation of the subsea manifold system. To perform a comprehensive analysis of the reliability of complex systems, a combination method of FMECA-FFTA (Failure Modes, Effects and Criticality Analysis - Fuzzy Fault Tree Analysis) is introduced in this study. Firstly, FMECA is used to accomplish a qualitative analysis of system reliability considering multifactorial failure modes, which included analyzing potential failure modes, causes of system failure, and evaluating the degree of hazard to the system through a risk matrix diagram. Then, FFTA is applied to build a fault tree model to divide the system into “system-subsystem-component” and determine the minimal cut sets for quantitative analysis of system reliability. In addition, fuzzy set theory is incorporated to improve the accuracy of handling uncertainty in quantitative reliability analysis. Finally, a qualitative and quantitative reliability analysis is conducted by using FMECA-FFTA method for subsea manifold system. The failure modes of the subsea manifold system are clearly identified, including high-risk modes such as external leakage, medium-high-risk modes such as fail to close/lock on demand, and medium-risk modes such as leakage of critical location, plugged, and effective measures should be taken to focus on preventive protection and regular testing for the high risk, medium-high risk and medium risk modes.

Experimental study on fluid-Induced vibration caused by backward erosion piping based on acoustic emission

Abstract Double-layer dike foundation is one of the most common stratum types with the highest probability of catastrophic failure in dike engineering, and the most important danger is backward erosion piping. The occurrence and development of piping need to be monitored by reliable technology. Therefore, the influence of different piping outlet forms on acoustic emission monitoring is explored by using a self-designed test device. The results show that the overall evolution process of ringing count and accumulated energy can be divided into two stages according to the time of piping. In the first and middle stages, the particle collision is caused by sand boiling at the outlet, and the measured value is small. In the later stage, piping channels appear, particle migration occurs, and the measured value is large. Moreover, the maximum impact value decreases with the increase of the piping outlet, and the cumulative energy growth rate of the three groups of tests in the early stage is the same, while the head difference required for the rapid growth stage is inversely proportional to the piping outlet.

Plant Leaf Disease Detection System using Machine Learning and Deep Learning: A Survey

Plant diseases are becoming more common, which is a serious threat to profitability of agriculture worldwide and requires the creation of reliable and efficient disease detection technologies. This work uses machine learning (ML) and deep learning (DL) approaches to give an extensive assessment of previous research on plant leaf disease identification. We examine and evaluate the many approaches used in the last several research, emphasizing the advantages, disadvantages, and useful uses of each. The study covers both sophisticated deep learning designs, such as convolutional neural networks (CNN) and recurrent neural networks (RNN), as well as more conventional machine learning techniques, such support vector machines (SVM) and decision trees. According to our research, plant leaf diseases can be more accurately identified and classified using deep learning techniques, especially CNNs, when applied to a variety of crop categories. The study also looks at the field’s obstacles and promising directions, highlighting the use of multifaceted approaches and real-time illness monitoring systems.

Plant Leaf Disease Detection System Using Machine Learning And Deep Learning: A Survey

Plant diseases are becoming more common, which is a serious threat to profitability of agriculture worldwide and requires the creation of reliable and efficient disease detection technologies. This work uses machine learning (ML) and deep learning (DL) approaches to give an extensive assessment of previous research on plant leaf disease identification. We examine and evaluate the many approaches used in the last several research, emphasizing the advantages, disadvantages, and useful uses of each. The study covers both sophisticated deep learning designs, such as convolutional neural networks (CNN) and recurrent neural networks (RNN), as well as more conventional machine learning techniques, such support vector machines (SVM) and decision trees. According to our research, plant leaf diseases can be more accurately identified and classified using deep learning techniques, especially CNNs, when applied to a variety of crop categories. The study also looks at the field’s obstacles and promising directions, highlighting the use of multifaceted approaches and real-time illness monitoring systems.

Rehabilitation of steel structures using innovative brace members equipped with YSPD damper

Earthquakes are serious risks to human life and infrastructure. An earthquake's influence on human life and its socioeconomic consequences highlight the need to investigate and create the most efficient and easily adaptable ways to minimize losses. The basic concept of different control mechanisms used for protecting structures from the destructive impacts of earthquakes is to dissipate the energy efficiently, therefore ensuring that the structure remains undamaged or sustains minimum damage. To achieve this purpose, the passive control mechanism is a particularly suitable and reliable technology as it doesn't rely on external power to actively dissipate energy. The present study proposes using a passive energy dissipation device called the Yielding Shear Panel Device (YSPD) for strengthening the current steel structures. The YSPD consists of a square hollow section (SHS) that houses a diaphragm plate. The fundamental concept of the YSPD involves harnessing the lateral deformation of a steel plate to absorb and disperse the seismic energy. The Bouc-Wen-Baber Noori (BWBN) material has been used for simulating the hysteresis force-deformation relationship of YSPDs by pinching. YSPDs are simulated as spring components that connect between the beam and the V-brace. A nonlinear time history dynamic analysis was performed to assess the alteration in the structural capacity with the setting up of YSPDs. The performance of the tested structure was assessed considering story drift, story displacement, story shear, column shear, and YSPD hysteresis loops. The results indicated that YSPD installation has improved the structure's capacity. However, the use of dampers resulted in significant drift in all stories, a reduction in total floor displacement, and a decrease in the shear force of the stories. However, the results demonstrated that the YSPD dampers effectively absorbed energy and exhibited stable hysteresis loops.

Effect of Al precursor’s properties on interactions with self-assembled monolayers for area selective deposition

Area selective deposition (ASD) is a high-precision atomic-level manufacturing technology that enables the development of bottom-up manufacturing methods in the future semiconductor field. The area selective deposition behavior of Al precursors on 1-octadecylthiol (ODT) passivated Cu/SiO2 surfaces was studied through experimental and theoretical analysis. The relationship between precursor steric hindrance, symmetry, penetration depth in ODT, and adsorption energy was elucidated. The loss of selectivity caused by different penetration depths of the precursor in ODT can be post-treated with acids or H2 plasma to remove the physisorption of precursor molecules between ODT chains, thereby improving the selectivity. Reliable ASD technology has been successfully applied to Cu/SiO2 patterns. Dimethylaluminum isopropoxide can selectively deposit about 10 nm of Al2O3 on SiO2 without detectable defects on the Cu area. This provides important insights into the choice of precursors in the ASD process and can extend its application to a wider range of device manufacturing schemes.

Integrated Sensing Platform Validated for the Efficient and On-Site Screening of Amine-Containing Illicit Drugs.

Efficient and reliable technologies for the on-site detection of illicit drugs are important in drug-facilitated crime investigations. However, the development of such technologies is challenging. Based on the synthetic optimization, introducing a boron ester functional group to the two furanic indicators endows the stimulus-responsive properties synergistically. The ring-opening reaction of the indicators in the presence of amine-containing illicit drugs generated well-known donor-acceptor Stenhouse adducts, accompanied by strong color changes. A small-size and lightweight laminated sensor was integrated based on the outstanding ratiometric variations of the two active furanic indicators. A prototype platform was fabricated equipped with a circuit control, a mini pump, and a signal processing system. A user-friendly detection and efficient screening of amine-containing illicit drugs, including phenethylamines, amphetamines, cathinones, and tryptamines in the liquid states were conducted. The ratiometric response of the sensor was linear in the concentration range of 2.1-10.6 μg·mL-1 for methamphetamine·HCl and methcathinone ·HCl. The detection limits for the two illicit drugs at the sublevel (ng·mL-1) were found to be 8.4 and 9.0 ng·mL-1, respectively. Double-blind field tests and different illicit drugs were evaluated with good screening capability. Successful trials showed the potential applications of the developed prototype platform for efficient and on-site analytical determination.

A Reconfigurable, Nonlinear, Low-Power, VCO-Based ADC for Neural Recording Applications.

Neural recording systems play a crucial role in comprehending the intricacies of the brain and advancing treatments for neurological disorders. Within these systems, the analog-to-digital converter (ADC) serves as a fundamental component, converting the electrical signals from the brain into digital data that can be further processed and analyzed by computing units. This research introduces a novel nonlinear ADC designed specifically for spike sorting in biomedical applications. Employing MOSFET varactors and voltage-controlled oscillators (VCOs), this ADC exploits the nonlinear capacitance properties of MOSFET varactors, achieving a parabolic quantization function that digitizes the noise with low resolution and the spikes with high resolution, effectively suppressing the background noise present in biomedical signals. This research aims to develop a reconfigurable, nonlinear voltage-controlled oscillator (VCO)-based ADC, specifically designed for implantable neural recording systems used in neuroprosthetics and brain-machine interfaces. The proposed design enhances the signal-to-noise ratio and reduces power consumption, making it more efficient for real-time neural data processing. By improving the performance and energy efficiency of these devices, the research contributes to the development of more reliable medical technologies for monitoring and treating neurological disorders. The quantization step of the ADC spans from 44.8 mV in the low-amplitude range to 1.4 mV in the high-amplitude range. The circuit was designed and simulated utilizing a 180 nm CMOS process; however, no physical prototype has been fabricated at this stage. Post-layout simulations confirm the expected performance. Occupying a silicon area is 0.09 mm2. Operating at a sampling frequency of 16 kS/s and a supply voltage of 1 volt, this ADC consumes 62.4 µW.

Self-fulfillment and Work in the Light of "The Acting Person" of Karol Wojtyla

This study focused on the philosophy of Karol Wojtyla in his book entitled “The Acting Person” about one of the activities of a human person, i.e. work itself. Although he did not dedicate any topic to human work, his very explanation of the action of the person as both subjective and personal is what human work is. Work, as lived experience, is one of the many actions a human person is capable of doing. On one side, despite the toilsome or burdensome character of human work, there exists a uniqueness in the person apart from beings. On the other, despite the uniqueness and value of work, there still exists a dehumanization from work, that of being replaced by faster and seemingly more reliable machinery or technology. However, work, as one of the many voluntary human actions, actually reveals the person and goes beyond his cosmological situatedness as simply a man. It is in the transcendence in action that changes these negative connotations of work putting the person as the subject and never the object of work. Work is a true manifestation of, first and foremost, our consciousness. The human person is not only conscious of his actions but even conscious of his conscious acting. Since the person is conscious of what he is doing, he is the efficient cause, that is, the active agent that brings about a series of effects. This conscious and efficacious acting brings about what Wojtyla would call self-determination, self-possession and self-governance. Lastly, work as one of the conscious and efficacious actions of a human person brings about self-fulfilment or in other words “felicity,” knowing that it is the same person who creates and contributes, in and through his work how and what it is to be human.

Establishing coherent momentum-space electronic states in locally ordered materials

Rich momentum-dependent electronic structure naturally arises in solids with long-range crystalline symmetry. Reliable and scalable quantum technologies rely on materials that are either not perfect crystals or non-crystalline, breaking translational symmetry. This poses the fundamental questions of whether coherent momentum-dependent electronic states can arise without long-range order, and how they can be characterized. Here we investigate Bi2Se3, which exists in crystalline, nanocrystalline, and amorphous forms, allowing direct comparisons between varying degrees of spatial ordering. Through angle-resolved photoemission spectroscopy, we show for the first time momentum-dependent band structure with Fermi surface repetitions in an amorphous solid. The experimental data is complemented by a model that accurately reproduces the vertical, dispersive features as well as the replication at higher momenta in the amorphous form. These results reveal that well-defined real-space length scales are sufficient to produce dispersive band structures, and that photoemission can expose the imprint of these length scales on the electronic structure.

Correlating NAD(P)H lifetime shifts to tamoxifen resistance in breast cancer cells: A metabolic screening study with time-resolved flow cytometry

Time-resolved flow cytometry (TRFC) was used to measure metabolic differences in estrogen receptor-positive breast cancer cells. This specialty cytometry technique measures fluorescence lifetimes as a single-cell parameter thereby providing a unique approach for high-throughput cell counting and screening. Differences in fluorescence lifetime were detected and this was associated with sensitivity to the commonly prescribed therapeutic tamoxifen. Differences in fluorescence lifetime are attributed to the binding states of the autofluorescent metabolite NAD(P)H. The function of NAD(P)H is well described and in general involves cycling from a reduced to oxidized state to facilitate electron transport for the conversion of pyruvate to lactate. NAD(P)H fluorescence lifetimes depend on the bound or unbound state of the metabolite, which also relates to metabolic transitions between oxidative phosphorylation and glycolysis. To determine if fundamental metabolic profiles differ for cells that are sensitive to tamoxifen compared to those that are resistant, large populations of MCF-7 breast cancer cells were screened and fluorescence lifetimes were quantified. Additionally, metabolic differences associated with tamoxifen sensitivity were measured with a Seahorse HS mini metabolic analyzer (Agilent Technologies Inc. Santa Clara, CA) and confocal imaging. Results show that tamoxifen-resistant breast cancer cells have increased utilization of glycolysis for energy production compared to tamoxifen-sensitive breast cancer cells. This work is impacting because it establishes an early step toward developing a reliable screening technology in which large cell censuses can be differentiated for drug sensitivity in a label-free fashion.