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Summary: The advanced technology in recent years that has achieved more attention among researchers and the social community is the wireless sensor network (WSN) that includes a number of nodes that are commonly distributed in remote zones. While deploying the WSN in huge areas, WSNs produce a massive amount of data. Thus, there is a significant need to process the data through efficient models. The data aggregation technique is the common solution widely employed to obstruct congestion on large‐scale WSNs. However, the demanding part of the data aggregation scheme is to mitigate the network overhead without affecting the system efficiency. Most of the data transmitted by sensor nodes are repetitious and thus result in high power consumption. Therefore, sensor nodes should utilize an efficient data aggregation model for data transmission that minimizes duplicate data. In order to maintain such complications, this article proposes a hierarchical Taylor quantized kernel least mean square (HTQKLMS) filter for aggregating data in WSN. For this purpose, WSN is initially simulated, and then data aggregation is accomplished using developed HTQKLMS filter. Additionally, the HTQKLMS is derived by amalgamating the hierarchical fractional quantized kernel least mean square (HFQKLMS) filter with the Taylor series. Here, the data prediction mechanism is done by employing HFQKLMS model that is an integration of quantized kernel least mean square (QKLMS) and hierarchical fractional bidirectional least mean square (HFBLMS). Apart from this, data redundancy is achieved by broadcasting needed data utilizing data detected at the destination. Furthermore, HTQKLMS approach has delivered a minimum energy consumption of 0.0333 J and less prediction error of 0.0326. [ABSTRACT FROM AUTHOR]

Mixed-reality simulation (MRS) is a new and advanced technology implemented in Educator Preparation Programs (EPP) across the United States. However, more research is needed on the effectiveness of MRS in EPPs and its impact on beginning teacher candidates. This study sought to determine the effect of teacher candidates after utilizing MRS and its impact on acquiring teaching pedagogical skills. Forty-five surveys collected from teacher candidates revealed two themes: the beneficial experience of MRS in an EPP and technology concerns. [ABSTRACT FROM AUTHOR]

Decentralized wastewater treatment systems are a potential solution to the water crisis. However, in addition to advanced technology, successful implementation of these systems requires broad public willingness to use them. This paper presents the results of a three-phase psychosocial intervention with the users of a business building where a decentralized wastewater treatment plant was installed. The intervention, motivated by complaints from users due to their lack of knowledge about the existence of the plant, aimed at understanding and improving users' perceptions of the building's decentralized system. In the first phase, we conducted a focus group with a sample of workers (n = 6) to understand their knowledge and perception of the building's decentralized wastewater treatment system. Once the main obstacles and facilitators were identified, we designed a second phase where a group of employees (n = 46) were exposed to environmental priming to improve attitudes toward the decentralized plant installed in the building. Finally, in the third phase, a bidirectional informative session was proposed, conducted by experts, to another group of workers (n = 25). Findings suggest that implementing specific psychosocial strategies, such as promoting environmental awareness and providing informative sessions, along with incorporating potential users throughout the process, contributes to better acceptance of the decentralized wastewater treatment plant. This work presents a real case in a pilot plant that can serve as a guide for addressing psychosocial resistance in similar projects. [ABSTRACT FROM AUTHOR]

The unique spin-optical properties of NV defects in SiC, coupled with silicon carbide's advanced technology compared to diamond, make them a promising candidate for quantum technology applications. In this study, using photoinduced pulse ESR at 94 GHz (3.4 T), we reveal the room temperature spin coherence of NV defects in 6H-28SiC, purified to reduce 29Si concentration to ≈1%, four times below its natural level. We demonstrate room temperature (300 K) Hahn-echo coherence time T 2 = 23.6 μs, spin–lattice relaxation time T 1 = 0.1 ms, and coherent control over optically polarized NV spin states through Rabi nutation experiments. We reveal long inhomogeneous dephasing time T 2 * = 1.5 μs, which is about five times greater than that measured for NV defects in SiC with natural isotopic content. Our observations highlight again the potential of NV defects in 6H-28SiC, which exhibit near-infrared optical excitation and emission properties compatible with O-band fiber optics, as promising candidates for applications in quantum sensing, communication, and computation. [ABSTRACT FROM AUTHOR]

Synthetic aperture radar tomography (TomoSAR) has emerged as an advanced technology for the rapid acquisition of three-dimensional information, with model solutions dependent on a specific complex least squares adjustment criterion. We design two TomoSAR imaging algorithms based on two adjustment criterions minimizing the square sum of the real and imaginary components of observation vector residual, and minimizing the square sum of the L2-norm of observation vector residual. Additionally, we propose a strong scatterer recognition method that combines amplitude thresholding and density-based spatial clustering of applications with noise to alleviate the low efficiency and excessive noise in real images. The simulated and practical experiments are conducted to evaluate the performance of algorithms. Results suggested that two algorithms perform similarly in parameter estimation accuracy and noise immunity for buildings with simple structures and single scatterer. However, for buildings with multiple scatterers, the algorithm derived by minimizing the square sum of the L2-norm from the observation vector residual exhibits more robustly than the other algorithm, accurately distinguishing multiple scatterers within pixels and reconstructing 3D scenes mirroring the actual ones. The results verify the effectiveness of the proposed strong scatterer recognition method and the importance of the adjustment criterion in TomoSAR imaging. [ABSTRACT FROM AUTHOR]

Microwave illusion, which can generate the scattering field of objects that don't exist to deceive the detecting devices, is an important and advanced technology in modern science. The conventional illusion device is limited by the narrow working band, non‐flat structure, or single functionality, which is inconvenient for electromagnetic integration. The newly multiplexing metasurfaces provide an effective method to achieve microwave illusion due to their excellent ability in wavefront tailoring. Here, a dual‐band microwave illusion enabled by multiplexing metasurface is proposed, and such a device can simulate two independent scattering fields of real objects at two separate frequencies by recording the near‐ and far‐field information. As a proof of concept, a meta‐illusion, realizing the electromagnetic information of the scaled‐down Sydney Opera House and Pyramid, is designed and fabricated. Microwave experiments are performed to demonstrate the predicted effects. The results show high correlation properties in both near‐ and far‐field characterizations, which is 83%, 80%, and 91%, 80% at two operating frequencies, respectively, verifying the high performance of the meta‐illusion. The findings may motivate the realizations of high‐performance meta‐illusions in other frequency domains and meta‐devices with complex functionalities. [ABSTRACT FROM AUTHOR]

In this article, we analyze how industry‐ and region‐specific characteristics influence individual‐level decisions on mobility within and between regions during the life cycle of the industry. Using uniquely detailed panel‐type data from the Finnish high technology sector, our analysis demonstrates that the influence of different regional features varies for different types of job changes and labor mobility and also according to the industry life cycle. We find that the classic agglomeration‐type arguments regarding labor search and matching only really operate in the early growth stages of an industry life cycle. These patterns change throughout the various stages of the industry life cycle, although in quite different ways according to different factors, and understanding how these patterns change helps to provide a richer understanding of the labor market roles of agglomeration and clustering. [ABSTRACT FROM AUTHOR]

The wide expansion of the meat industry generated tremendous amounts of animal-based waste. Discarded beef tallow (DBT) is one of those prevalent lipid-rich wastes disposed of by slaughterhouses, meat processing units, and tanneries. The current study utilized the advanced technology of supercritical CO2 (SC-CO2) to extract lipid content from DBT for biodiesel production through transesterification. The effects of SC-CO2 parameters on the extraction rate were investigated over ranges of (32–80°C) for temperature, (10–50 MPa) for pressure, and (15–150 min) for treatment time. Using response surface methodology (RSM), both processes of SC-CO2 and transesterification were optimized. The highest extraction rate was 86.10%, obtained at the experimental conditions of 60°C for temperature, 30 MPa for pressure, and 120 min for treatment time. For the transesterification, the maximum yield of biodiesel was 95.15%, obtained at the reaction conditions of 1:7.5, 1.16 wt%, 58°C, and 72 min for lipid to methanol molar ratio, catalyst ratio, temperature, and time, respectively. The outcomes of the kinetic and thermodynamic analyses showed that the SC-CO2 extraction was an endothermal, unspontaneous, and temperature-dependent process. The characteristics of the synthesized biodiesel largely comply with the ASTM D6751 and EN 14,214 standards. The findings of the current study confirm the viability of SC-CO2 to extract lipids from DBT as a low-cost feedstock for biodiesel production. HIGHLIGHTS: Lipids were extracted from discarded beef tallow using supercritical CO2. Kinetics & thermodynamics analyses were conducted for the lipid extraction. Dependent and independent variables were optimized by RSM. Biodiesel fuel was synthesized from the separated lipids. [ABSTRACT FROM AUTHOR]

In the evolving landscape of international politics, the ascent of small and medium-sized (SMS) states in knowledge industries is notable. As these states, exemplified by Israel, Sweden, Singapore, and the United Arab Emirates, harness advanced technological capabilities, their global influence grows. Unlike great powers, SMS states face a heightened risk in developing advanced technology due to limited national resources and the absence of technological redundancies. Our examination of Israel's experience in the satellite, cybersecurity, and artificial intelligence industries serves as a case study demonstrating how an SMS state can establish competitive knowledge sectors. These technologically advanced SMS states attain a status akin to middle powers, challenging conventional perceptions. Analyzing Israel's commitment to securing these technological fields reveals government intervention aimed at cultivating sustainable knowledge industries and preserving critical knowledge. While diverse motivations drive the technological development of SMS states, their capabilities reshape conventional notions of middle powers and global power distribution. [ABSTRACT FROM AUTHOR]

4D printing is an advanced technology that integrates the mechanics design and active materials into 3D printing to create objects with time‐evolving transformation. However, the commonly used active materials, such as shape memory polymers or hydrogels, make it challenging to simultaneously realize two‐way shapeshifting and high stiffness in 4D printed structures, constraining its application in engineering areas such as robotics, morphing structures, etc. Herein, inspired by human musculoskeletal structure, a 4D printing strategy that integrates two‐way shapeshifting liquid crystal elastomer and amorphous shape memory polymer to realize reversible actuation and tunable stiffness via sequential thermal control is proposed. Through numerical analysis and experimental investigation, the mapping relationship among structural deformation, material property, and geometric design is established, allowing to seek out the optimized thickness ratio and material properties that lead to high shape fixity (81%) and complete shape recovery (100%). To demonstrate the potential applications, a variable stiffness hook capable of wrapping and lifting heavy objects through helical transformation is realized. This design strategy can potentially inspire the development of 4D printing toward load‐bearing soft machines. [ABSTRACT FROM AUTHOR]

This article re-examines why and how China abandoned one of the core ideological principles of the Mao era: self-reliance. This did not occur after 1978 and Deng Xiaoping’s ascent to paramount power, but instead from 1971, when technocratic Chinese leaders redefined self-reliance to include importing advanced technology to better develop China’s resources, including for export — a change that anticipated the policies of post-1978 Reform and Opening. The article argues that this redefinition was possible because Sino-American rapprochement and the end of the US technology and economic embargo on China provided previously unprecedented levels of access to US and Western technology. [ABSTRACT FROM AUTHOR]

Human Enterovirus 71 (EV71) has emerged as one of the predominant causative agents of hand, foot and mouth disease (HFMD) with global impact. Despite the inactivated vaccine being licensed, other vaccine candidates based on advanced technology platforms are under development. In this report, we rationally designed and constructed two DNA-launched live attenuated vaccine candidates (pDL-EV71) under the control of specific promoters. In vitro and in vivo transfection with pDL-EV71 driven by the CMV promoter successfully yielded fully infectious EV71. More importantly, the administration of pDL-EV71 did not cause clinical symptoms following intracranial or intramuscular inoculation in neonatal and IFNα/βR-/- mice, demonstrating its safety profile. Moreover, a single-dose or two-dose immunization with pDL-EV71 elicited robust neutralizing antibodies against EV71 as well as an antigen-specific cellular response in mice. A single-dose immunization with 10 μg of pDL-EV71 conferred complete protection against lethal EV71 infection in neonates born to immunized maternal mice. Overall, our present results demonstrate that pDL-EV71 is a safe and effective vaccine candidate against EV71 for further development. [ABSTRACT FROM AUTHOR]

Copyright of Relaciones Internacionales (1699-3950) is the property of Autonomous University of Madrid, Spain, International Relations Studies Group (GERI) Law Faculty and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

High-tech whiteleg shrimp ponds (Litopenaeus vannamei) (intensive and superintensive) are rapidly developing. The rapid development is due to the increasing demand for world shrimp, the mastered cultivation technology, and the vast potential of land in Indonesia. The Indonesian government has even made various regulations to support increased sustainable shrimp production. However, the regulation is still sectoral and cannot be implemented by all stakeholders and investors in aquaculture. In addition, investors have not practiced several stages of activities to ensure environmental safety and the success of shrimp farming. As a result, production targets have not been achieved, and the threat of high potential waste is wasted on the aquatic environment. Therefore, a role model is needed to govern high-tech whiteleg shrimp pond development to ensure all shrimp production improvement system instruments can run well. Based on this, research has been conducted to create a role model for developing high-tech whiteleg shrimp ponds (Litopenaeus vannamei). The research used survey methods and group discussion forums (FGDs). The results showed that there are four main components that must exist and synergize in the role model of governance for the development of high-tech whiteleg shrimp ponds: land carrying capacity, cultivation facilities, pond management, and government regulations. [ABSTRACT FROM AUTHOR]

This study aimed to examine the different latent profiles of technology addiction in young adults, and the criteria for belonging to these profiles, in relation to sociodemographic factors (gender and SES) and technology use status (daily social network usage time, daily instant messaging usage time, daily online gaming usage time, daily website usage time, and connection location). Data were collected from a sample of 1,431 young adults [988 (69.1%) female, 443 (30.9%) male]. Latent Profile Analysis (LPA) was used to identify the latent profiles, and Multinomial Regression Analysis was employed to examine the relationships between the latent profiles and sociodemographic and technology use. The LPA revealed four latent profiles of technology addiction in young adults: "Non-Addicts (NA)", "Moderate Technology Addicts-Gamers (MTAG)", "High Technology Addicts-Non-Gamers (HTANG)", and "High Technology Addicts-Gamers (HTAG)". The criteria for belonging to these four profiles were statistically significantly related to sociodemographic and technology use factors, except for connection location, and age. These findings provided further support for our knowledge about planning programs or multi-layered intervention models to prevent technology addiction in young adults. [ABSTRACT FROM AUTHOR]

This study introduces a novel thermoacoustic (TA) focusing system enhanced by Airy beam-based acoustic metasurfaces, significantly improving acoustic focusing and efficiency. The system integrates a TA emitter, fabricated from carbon nanotube (CNT) films, with a binary acoustic metasurface capable of generating quasi-Airy beams. Through finite element simulations, the system's heat conduction, acoustic focusing, and self-healing properties were thoroughly analyzed. The results demonstrate that the system achieves superior sub-wavelength focusing, tunable focal length via frequency control, and robust self-healing, even in the presence of obstacles. These findings address current limitations in TA emitters and suggest broader applications in medical ultrasound and advanced technology. [ABSTRACT FROM AUTHOR]

This paper presents the results of the technical validation of an innovative prototype for drying alfalfa bales. It is based on a 4.1 kW Heat Pump (HP) that uses an advanced technology (optimized for extracting the humidity from the air) and is directly powered by a 6.6 kWp PV generator without grid or batteries support. The main technical challenges of this work were managing solar irradiance fluctuations due to cloud-passing and achieving good drying efficiency. The prototype has been validated for two consecutive drying campaigns in La Rioja (Spain). There were no abrupt stops generated by cloud-passing. The PRPV, which evaluates the performance of the PV system only during the periods when the PV energy can be used by the HP unit, presented values of 0.82 and 0.85, comparable to a well-performing grid-connected PV system. Although the bales' initial relative humidity (RH) ranged from 18 to 30%, all but one of them presented a final RH below 16%, which is the limit point to avoid fermentation. The drying times ranged from 1 to 5 h, and the specific energy consumption per liter of water extracted, from 0.7 to 1.46 kWh/L. These values are comparable to traditional diesel and grid-powered systems. It is worth noting that the agricultural drying market represented USD 1.7 billion in 2023. [ABSTRACT FROM AUTHOR]

Displays have become ubiquitous in our modern and highly interconnected lives. Complex vacuum processed multi‐stacks are widely integrated into high tech, high value products such as smart phones, while solution processed large area single‐layer OLEDs appear more adequate for basic applications focusing on recyclability such as packaging, road signage, advertising, and single‐use health care products. In this context, we report herein the design, synthesis, and characterization of an accessible series of oligothiophenes end‐capped triphenylamines that were preprepared by atom‐economical direct (hetero)arylation reactions and successfully used as emitter in solution processed devices, from lab scale to large area printed and flexible demonstrator. [ABSTRACT FROM AUTHOR]

Cracks exist in the majority of components of ancient Chinese timber structures and have led to serious mechanical property degradation problems, threatening the safety of the whole structures and making the cracks' detection for wooden components a necessity. With the rapid development of intelligent protection technology of cultural buildings, it is important to establish a scientific identification and quantification method for cracks in wooden components to replace traditional manual detection techniques. Deep learning is precisely such an advanced technology. In this study, images of cracked wooden components were first collected from the Yingxian wooden pagoda and the crack characteristics were analyzed. A dataset for crack segmentation was established using a total of 501 images of cracked wooden components, including a training dataset of 450 images and a validation dataset of 51 images. Based on the mathematical principles of deep learning and the fully convolutional neural networks (FCNN), a deep fully convolutional neural network (d‐FCNN) model was constructed based on encoding and decoding methodology. Four model indicators, pixel accuracy (PA), average pixel accuracy (mPA), mean intersection over union (mIoU), and F1‐score were analyzed to train the model and determine the optimal model parameters, including learning rate, batch size, and epoch. It concluded that the optimal initial learning rate takes the value of 10−4, batch size of 6, and epoch of 100, achieving the average accuracy of 78.8%. Further, based on the pixel's accumulation principle, a quantitative calculation method for crack length and maximum width was proposed. Two cracked wooden columns were prepared, and crack image identification and quantification experiments were conducted to verify the correctness of the constructed d‐FCNN model and the proposed crack quantification method. The results show that the model is suitable for crack intelligence detection, identification, and quantification of cracked wooden components. [ABSTRACT FROM AUTHOR]

ABSTRACT Recent work in philosophy of technology has come to bear on the question of responsibility gaps. Some authors argue that the increase in the autonomous capabilities of decision‐making systems makes it impossible to properly attribute responsibility for AI‐based outcomes. In this article we argue that one important, and often neglected, feature of recent debates on responsibility gaps is how this debate maps on to old debates in responsibility theory. More specifically, we suggest that one of the key questions that is still at issue is the significance of the reactive attitudes, and how these ought to feature in our theorizing about responsibility. We will therefore provide a new descriptive categorization of different perspectives with respect to responsibility gaps. Such reflection can provide analytical clarity about what is at stake between the various interlocutors in this debate. The main upshot of our account is the articulation of a way to frame this ‘new’ debate by drawing on the rich intellectual history of ‘old’ concepts. By regarding the question of responsibility gaps as being concerned with questions of metaphysical priority, we see that the problem of these gaps lies not in any advanced technology, but rather in how we think about responsibility. [ABSTRACT FROM AUTHOR]

A seminal component of systems thinking is the application of an advanced technology in one domain to solve a challenging problem in a different domain. This article introduces a method of using advanced computer vision to solve the challenging signal processing problem of specific emitter identification. A one-dimensional signal is sampled; those samples are transformed into to two-dimensional images by computing a bispectrum; those images are evaluated using advanced computer vision; and the results are statistically combined until any user-selected level of classification accuracy is obtained. In testing on a published DARPA challenge dataset, for every eight additional signal samples taken from a candidate signal (out of many thousands), classification error decreases by an entire order of magnitude. [ABSTRACT FROM AUTHOR]

The relationship between China (PRC) and the United States (USA) has reached an unprecedented level of tension, mainly due to economic and technological rivalry. This study introduces an original quantitative method, the Pentagon of Technological Competitiveness of Economy (PTCE) to measure the technological competitiveness of both countries from 2000 to 2020. The findings reveal that while the USA remains a global technological leader, the PRC is emerging as a formidable challenger. Although the USA still holds the lead, signs of decline are visible, while the PRC exhibits a remarkable upward trajectory in technological competitiveness. The findings provide actionable recommendations for policymakers. To reinforce its position as the unrivaled technological leader, the USA should prioritize enhancing capabilities in areas such as patents, scientific articles and the export of high technology and STEM-related products. For the PRC there is an unprecedented opportunity to surpass the USA in technological leadership by strategic investments in research, innovation and human capital development. The novelty of this research lies in two main areas: (i) its significant contribution to competitiveness analysis through the introduction of the PTCE method and (ii) its provision of a comprehensive assessment of the shifting technological dynamics between the USA and the PRC. [ABSTRACT FROM AUTHOR]

Extrusion-based 3D bioprinting techniques are revolutionizing bioengineering by facilitating the creation of complex 3D microstructures. This review offers a thorough overview of extrusion-based 3D bioprinting methods, particularly highlighting the innovative electric-assisted coil-write 3D bioprinting technology. The review begins by explicating the fundamental principles underlying various extrusion-based 3D bioprinting technologies. It covers the printing equipment composition, suitable materials for 3D bioprinting, and the latest breakthroughs in technology. A critical aspect of this review is the in-depth comparison of the strengths and weaknesses associated with each 3D bioprinting approach. The electro-microfluidic extrusion method and the electric-assisted coil-write 3D bioprinting technology are highlighted. This advanced technology successfully overcomes the limitations of conventional extrusion-based methods, notably in the precise printing of intricately curved line structures with high resolution and speed. This method ingeniously integrates mechanical motion for creating microscale features with electrical coiling for sub-micron details, thus achieving remarkable printing speeds and structural complexity. This review concludes by exploring the potential applications and future advancements of this state-of-the-art technology. It underscores the ability of electric-assisted coil-write 3D bioprinting to develop pioneering materials and micro-devices for a variety of technological sectors, highlighting its transformative impact in bioengineering. [ABSTRACT FROM AUTHOR]

This study posits that U.S.-China technology competition has promoted the spread of techno-economic statecraft in East Asia. The emergence of techno-economic statecraft in East Asia requires systematic analysis because it affects not only the dynamics of U.S.-China technology competition but also the restructuring of the regional order. Since both the United States and China do not have complete self-sufficiency in the high-tech innovation ecosystem, it has become an urgent task for them to reduce their vulnerability to winning technological competition. Against this backdrop, East Asian countries have emerged as actors playing an important role in technological competition. Since East Asian countries are key players in the supply chain of high-tech industries, cooperation with East Asian countries has emerged as a factor that can influence the landscape of U.S.-China technology competition. Based on these observations, this study aims to explain the following four phenomena: First, it explains the process by which the United States and China seek to securitize high technology as a means of reducing their own structural vulnerabilities while redrawing new boundaries for cooperation with East Asian countries. Second, I argue that U.S.-China technology competition has accelerated the rise of techno-economic statecraft in East Asia. Third, I assert that there are significant differences in the techno-economic statecraft pursued by East Asian countries in the U.S.-China technology competition. Fourth, the divergence of techno-economic statecraft in East Asian countries has created systemic effects in the regional order. [ABSTRACT FROM AUTHOR]

We investigate the moderating effect of an indigenous Indonesian concept, kekeluargaan (kinship ties and obligations), on the digital transformation (DT) of the warung, a traditional family microbusiness in Indonesia. Our study is structured as a multi‐case study: we assessed how five warungs, to varying degrees, engaged in DT. Socio‐technical systems theory guides the data collection via semi‐structured interviews and observations. The data is analyzed through codification to look for themes and patterns from the multiple units of analysis. The findings show that the growth mindset of warung owners influences how they solve business problems, ensure operational efficiency, and increase profit. Some create an effective structure in operating their warung by working with their family members. Owners with a high technology mindset successfully learn and adapt the technology. We theorize that kekeluargaan plays a moderating role for the owner where technology‐related tasks are concerned. We found that when kekeluargaan is present, it positively moderates the owner's engagement in technology‐related tasks. However, when kekeluargaan is absent, the moderating effect is low. The findings extend the literature on DT for microbusinesses with indigenous cultural factors that should be considered to successfully transform a traditional business. [ABSTRACT FROM AUTHOR]

The cost landscape in advanced technology systems is shifting dramatically. Traditionally, hardware costs took the spotlight, but now, programming and debugging complexities are gaining prominence. This paper explores this shift and its implications, focusing on reducing the cost of programming complex robot behaviors, using the latest innovations from the Generative AI field, such as large language models (LLMs). We leverage finite state machines (FSMs) and LLMs to streamline robot programming while ensuring functionality. The paper addresses LLM challenges related to content quality, emphasizing a two-fold approach using predefined software blocks and a Supervisory LLM. [ABSTRACT FROM AUTHOR]

Microsatellites have significantly impacted space missions by offering advanced technology at a low cost. This study introduces an attitude determination and control algorithm for agile whiskbroom scanning maneuvers in microsatellites to enable wide-swath target detection for low-Earth-orbit microsatellites. First, an angular velocity calculation model for agile whiskbroom scanning is established. A methodology has been developed to calculate the maximum available time for whiskbroom scanning from one side of the sub-satellite point to the other while ensuring the seamless joining of adjacent strips to avoid missing targets. Thereafter, a gyro- and magnetometer-based cubature Kalman filter is put forward for microsatellite attitude estimation. Furthermore, for attitude control, a hybrid manipulation law capable of preventing singularities and escaping singularity surfaces is designed to ensure high-precision torque output from the control moment gyroscopes (CMGs) used as actuators. The benefits of the linear sliding mode and fast terminal sliding mode are integrated, and a non-singular sliding surface is designed, yielding a non-singular fast terminal sliding mode attitude control algorithm for tracking the desired trajectory. This algorithm effectively suppresses chattering and enhances dynamic performance without using a switching term. A semi-physical simulation experiment system is also conducted on the ground to validate the proposed algorithm's high-precision tracking of the planned whiskbroom scanning path. The experimental results demonstrate an attitude angle control accuracy of 4 × 10−2 degrees and angular velocity control accuracy of 0.01°/s and thus the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Copyright of Hacettepe University Journal of Economics & Administrative Sciences / Hacettepe Üniversitesi Iktisadi ve Idari Bilimler Fakültesi Dergisi is the property of Hacettepe University, Faculty of Economic & Administrative Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Magneto-Rheological (MR) automotive suspension represents the most advanced technology currently available for enhancing passenger comfort through intelligent fluid behaviour. This work employed a Modified Bouc-Wen model to create a mathematical representation of a single MR vehicle suspension and compared its ride performance to that of passive suspension systems. The model was formulated and solved using second-order linear differential equations, with MATLAB software utilized to visualize the results. The maximum vertical displacement for the single MR mathematical model in this work was 0.031 m, while the minimum was -0.0124 m. At the minimum position, the vertical displacements for the passive model were 0.0532 m and -0.0133 m. The results demonstrated that the vertical displacement variation was similar for both the mathematical model and the passive system. All displacements obtained from the mathematical modeling of the single MR system were close to its mean of 0.000875 m (nearly zero). There was reduced vibration when zero displacement was achieved. It was concluded that MR damper significantly improved car suspension performance compared to passive solutions. This paper developed a single MR vehicle suspension system using the Modified Bouc-Wen model in a Proton Preve. [ABSTRACT FROM AUTHOR]

The growth of advanced technologies has been rising in recent years, which affects business operations throughout the supply chain. The smart warehouse is one of many technologies that increase warehouse management efficiency, for instance, increasing accuracy and reducing operating costs and processing times. Smart warehouse technologies are expected to be critical factors for effectively entering the fourth industrial revolution in Thailand. Currently, the utilization of smart warehouses in Thailand is not widespread; however, many organizations view such technologies as integral parts that will change the entire industry in Thailand. This research project explores and analyzes innovative warehouse technologies and their requirements for various industry sectors in Thailand. In addition, both qualitative and quantitative methods are employed to gather data. In-depth interviews of executives and warehouse managers are conducted, together with self-administered questionnaire surveys, to both smart warehouse users and providers. TOWS Analysis is applied to identify appropriate strategic options. Policy recommendations to effectively improve the unitization of smart and innovative warehouse technologies are also discussed. [ABSTRACT FROM AUTHOR]

This article is about Three-dimensional (3D) printing technology or additive manufacturing which is an advanced technology developed during the late 20th century that involves construction of a threedimensional object from a CAD model or a digital 3D model. In recent times, rapid advancements in the three-dimensional (3D) printing technology, precise and customised manufacturing has been achieving gradual, benefitting biomedical application, especially in stomatology clinical practice. It has been broadly connected to the areas of prosthodontics, orthodontics, and maxillofacial surgery strategies, giving exact, proficient operation and promising treatment results. Recently the 3D printing industry has made huge strides in medical devices, implant materials, and cell printing by lowering manufacturing costs while improving printing accuracy and speed. [ABSTRACT FROM AUTHOR]

The objective of this study was to examine the effect of a training program utilizing action perception technology (PAD) tools on improving the motor reaction times and neuromuscular capabilities of the upper and lower limbs compared to a traditional training program. Twenty-four female volleyball players competing in the Italian national championship were randomized into two groups of 12 athletes each: an experimental group (EG) and a control group (CG). A preliminary analysis confirmed the absence of significant differences in age and anthropometric characteristics between the groups. All the players underwent an initial battery of tests (pre-test), including Reaction Time simple Upper and Lower Limb (RTsUL and RTsLL) and Tapping Upper and Lower Limb (TUL and TLL). During a 6-week training program, the experimental group used exercises with a technological system of illuminated disks, while the control group followed the traditional training methods without advanced technology. At the end of the program, both groups were subjected to final tests (post-test). The main results show that after 6 weeks, both groups improved their performance compared to the initial tests. However, EG achieved significantly better results than CG in every test, with significant reductions in average times (ip%) of −14.9% in RTsUL (DX = −0.072 s, t = 23.2, p < 0.05, d = 6.7), −14.9% in RTsLL (DX = −0.091 s, t = 44.0, p < 0.05, d = 12.7), −10.6% in TUL (DX = −0.622 s, t = 42.0, p < 0.05, d = 12.1), and −10.7% in TLL (DX = −0.983 s, t = 43.1, p < 0.05, d = 12.4). The use of light-based perception–action technology devices in volleyball training has shown potential for significantly improving movement speed and reaction time. However, further research is needed to determine whether these improvements actually translate into enhanced overall performance in competitive contexts compared to the traditional training methods. [ABSTRACT FROM AUTHOR]

The main objective of this study is to analyze and provide an interpretation of Psalm 23 within the framework of Christian Education in the post-human era. Employing a qualitative methodology, the research utilizes a combination of literature study and biblical exegesis to gain a comprehensive understanding of the text. By employing an interpretative approach that involves exposition and critical analysis, the study engages with relevant literature to discuss the significance of Psalm 23 in education. The psalm portrays a profound trust in God's guidance, care, and provision, emphasizing the importance of these theological themes in the field of education. In the context of the rapidly evolving challenges presented by advanced technology and the blurring of human-machine boundaries, the timeless wisdom of Psalm 23 serves as a moral compass and provides valuable insights for educators to navigate these complex issues. [ABSTRACT FROM AUTHOR]

High-resolution and thermal infrared hyperspectral data acquired from the Thermal Infrared Airborne Spectrographic Imager (TASI) have been recognized as efficient tools in geology, demonstrating significant potential for rock discernment. Deep learning (DL), as an advanced technology, has driven substantial advancements in lithological mapping by automatically extracting high-level semantic features from images to enhance recognition accuracy. However, gathering sufficient high-quality lithological samples for model training is challenging in many scenarios, posing limitations for data-driven DL approaches. Moreover, existing sample collection approaches are plagued by limited verifiability, subjective bias, and variation in the spectra of the same class at different locations. To tackle these challenges, a novel sample generation method called multi-lithology spectra sample selection (MLS3) is first employed. This method involves multiple steps: multiple spectra extraction, spectra combination and optimization, lithological type identification, and sample selection. In this study, the TASI hyperspectral data collected from the Liuyuan area in Gansu Province, China, were used as experimental data. Samples generated based on MLS3 were fed into five typical DL models, including two-dimensional convolutional neural network (2D-CNN), hybrid spectral CNN (HybridSN), multiscale residual network (MSRN), spectral-spatial residual network (SSRN), and spectral partitioning residual network (SPRN) for lithological mapping. Among these models, the accuracy of the SPRN reaches 84.03%, outperforming the other algorithms. Furthermore, MLS3 demonstrates superior performance, achieving an overall accuracy of 2.25–6.96% higher than other sample collection methods when SPRN is used as the DL framework. In general, MLS3 enables both the quantity and quality of samples, providing inspiration for the application of DL to hyperspectral lithological mapping. [ABSTRACT FROM AUTHOR]

Calcitonin gene-related peptide monoclonal antibodies (CGRP mAbs) are novel high-cost treatments for the prevention of migraine. This study presents data on utilization, expenditure, and treatment patterns with CGRP mAbs available under a managed access protocol in Ireland, to a cohort of treatment refractory patients (failed 3 or more previous treatments) with chronic migraine. Data were extracted from the Primary Care Reimbursement Service High Tech claims database and special drug request online system and analyzed using Microsoft Excel and SAS. Treatment persistence was evaluated by refill patterns, and adherence was evaluated using the proportion of days covered method. Expenditure data were extracted directly from the database. Between September 1, 2021 and April 30, 2023, 1517 applications for reimbursement approval for a CGRP mAb were received; 1458 (96.1%) were approved for reimbursement. Total expenditure on CGRP mAbs in year 1 (September 1, 2021 to August 31, 2022) was €3.2 million. The majority of patients initiated treatment with fremanezumab (60.8%) or erenumab (37.1%). Almost 90% of patients were considered adherent, and treatment persistence was high, with more than 75% of patients receiving more than 12 months of treatment in our 18-month study time frame. This study demonstrates the importance of active health technology management, after reimbursement, in enabling cost-effective use of high-cost treatments while providing budget certainty for the healthcare payer. High levels of adherence and persistence suggest that treatment is successfully targeted in situations which unmet clinical need is greatest. • Calcitonin gene-related peptide monoclonal antibodies are novel, high-cost treatments for the prevention of migraine. • In 1 year of reimbursement in Ireland, the total expenditure on calcitonin gene-related peptide was €3.2 million, with the majority of approved patients being highly treatment adherent. • Health technology management can ensure cost containment while maintaining access to treatment in situations which unmet clinical need is greatest. [ABSTRACT FROM AUTHOR]

A new decoupling element technology is used to create a tiny circular patch mutiple input multiple output (MIMO) antenna measuring 20 × 25 × 1.6 mm3. A simple split‐ring resonator (SRR) metamaterial design with adjustable inner ring inductance and capacitance allows MIMO antennas to operate across several frequency bands. Tunable‐split ring resonators (T‐SRRs) are small and improve antenna element isolation. The proposed MIMO system provides isolation larger than 20 dB from 5.93 to 12.63 GHz. It is useful for radar applications since it includes the C‐band upper link (5.925–6.425 GHz) and the X‐band (8–12 GHz). With good tuning and network structure decoupling, antennas can operate in dual bands with isolation levels below −15 dB. Over 85% radiation efficiency and 72% miniaturization were achieved in the proposed MIMO antenna. The antenna has good radiation and diversity performance, including an envelope correlation coefficient < 0.1 and a diversity gain of 9.98 dB. These qualities make it suitable for advanced technology. [ABSTRACT FROM AUTHOR]

In tracking scenarios involving groups with dense targets, achieving effective data association is challenging due to mutual occlusion and interference among targets. The complexity of the tracking problem is further exacerbated in low‐observable environments by the increase in false alarm rates. The track‐before‐detect (TBD) is an advanced technology for detecting and tracking low‐observable targets, effectively mitigating data association problems by integrating multi‐frame echo data. However, the existing multi‐target TBD algorithms typically assume that the targets are spatially separated and are not suitable for scenarios involving group targets. A group target maximum‐likelihood probabilistic data association (GT‐ML‐PDA) algorithm, based on the concept of TBD, is proposed to track group targets effectively in low‐observable environments. The proposed algorithm divides group target tracking into two stages: group centre trajectory estimation and individual target trajectory estimation. To enhance the performance of the proposed algorithm, two strategies are suggested: modifying the equivalent measurements and extracting independent measurement sets for individual targets. Simulation results demonstrate that the proposed algorithm is capable of effectively tracking numerous individual targets within a group, even in the presence of heavy clutter. [ABSTRACT FROM AUTHOR]

Soft robots have been advancing rapidly, but their control is still limited by rigid control elements. Soft valves offer a solution to this problem by enabling soft robots to no longer rely on rigid control elements. They have become an emerging research topic in soft robotics. However, with a large number of publications on soft valves, it may be challenging for researchers to quickly grasp the advanced technology related to soft valves. To address this issue, this article summarizes the current state of development in soft valves. The design principles and applications of soft valves in terms of structures and materials are discussed, along with the modeling ideas for soft valves. Finally, the current challenges faced by soft valves are outlined, and potential solutions to these problems are proposed. [ABSTRACT FROM AUTHOR]

"New quality productivity" is an important term put forward by General Secretary Xi Jinping in September 2023 during his visit and research in Heilongjiang. It is a form of productivity relative to traditional productivity, characterized by high technology, high energy efficiency and high quality, with science and technology innovation as the core driving force, and with a wide range of permeability and integration. To develop new quality productivity, it is inseparable from scientific and technological innovation and the development of new industries. Digital economy and intelligence are important paths to develop new quality productivity. The purpose of this paper is to explore the path and its impact of digital intelligence innovation on productivity enhancement in the Greater Bay Area from a multi-dimensional perspective. The study first starts with the policy environment, outlines the policy background of the Greater Bay Area, comprehends the formation and development of the digital economy, and analyzes in depth how policies promote digital innovation. On this basis, the paper explores the specific impact of digital intelligence innovation on productivity and its path from three perspectives: technological, social and cultural. Under the technological perspective, this paper focuses on the technology -- driven mechanism of digital intelligence innovation, including its direct impact on the optimization of industrial structure and productivity enhancement, and analyzes in detail the breakthroughs in major technological fields and their role in promoting the regional economy. Through technological innovation cases, it demonstrates how digital innovation can enhance productivity at the technological level and inject new vitality into the economy of the Greater Bay Area. The social perspective focuses on how digital intelligence innovation can enhance social governance, drive social benefits and public services, and explore the role of digital intelligence innovation in promoting social inclusion and narrowing the digital divide. By analyzing the specific practices and effects at the social level, it reveals the important role of digital intelligence innovation in social development. The cultural perspective analyzes the integration of digital intelligence innovation with regional culture and explores its role in promoting the cultural industry. It demonstrates the specific practices of the integration of culture and technology through typical cases, emphasizes the importance of regional cultural identity and innovation atmosphere, and proposes how to further enhance the productivity of the Greater Bay Area through cultural innovation. In the comprehensive analysis section, this paper integrates the analysis results from various perspectives and proposes the future development trend of digital intelligence innovation and its long-term impact on productivity enhancement in the Greater Bay Area. Finally, based on the findings, this paper proposes a series of policy recommendations and optimization paths, including strengthening policy support, promoting technological research and development, and fostering social inclusiveness and cultural innovation, with a view to providing scientific references and practical guidance for the future development of the digital intelligence economy in the Greater Bay Area. [ABSTRACT FROM AUTHOR]

In a construction project, especially in risky environments, subcontractors are considered as important as the main contractor since most work is carried out by them. A crucial step in building projects is choosing the finest subcontractor. When choosing subcontractors, a variety of considerations must be taken into account. A poor choice of subcontractors might cause a lot of issues when the job is being done. These include subpar work and project length delays. Many things influence this process. From earlier studies, variables that affect the choice of a subcontractor have been compiled. The main aim of the paper is to predict the failure of the subcontractor by using a mix of several advanced technology as BIM, machine leaning and building a system. The methodology of the paper is first to use BIM to see the mistakes and unqualified quantity estimation by the subcontractors which lead to increase the cost of the projects and hence failures of the projects. The second step is to identify primary reasons for subcontractors' failure and identify and evaluate the major reasons why contractors fail on industrial projects in Iraq. The third step is to predict the performance of the subcontractor using three algorithms (logistic regression, decision tree and Naive Bayes) with data collected from 234 projects and see how the wrong selection of the subcontractors leads to incomplete projects in the future. The variables that used in the paper include the most effective one, as change order effect directly on the projects performance as well as cost, time, deviation, type of projects and the rate of project completion, the low the percentage of completion the worse the performance. The final step is to develop a system to manage the subcontract in different projects stage. The results show that there is a different in the quantity estimated between the actual and the estimated range between (5% to 15%) in several item of the building, which consider high. the best algorithms for the is Naive Bayes as give accuracy about 97%. [ABSTRACT FROM AUTHOR]

Gastroesophageal reflux disease (GERD), a prevalent clinical condition, is often attributed to aberrant esophageal motility, leading to gastric content reflux and associated symptoms or complications. The rising incidence of GERD presents an escalating healthcare challenge. Endoscopic and esophageal reflux monitoring can provide a basis for the diagnosis of patients with gastroesophageal reflux disease, but when the diagnostic basis is at an inconclusive value, some additional supportive evidence will be needed. Advanced technology is the key to improving patient diagnosis, accurate assessment, and the development of effective treatment strategies. High-resolution esophageal manometry (HREM) and endoscopic functional lumen imaging probe (EndoFLIP) represent the forefront of esophageal motility assessment. HREM, an evolution of traditional esophageal manometry, is considered the benchmark for identifying esophageal motility disorders. Its widespread application in esophageal dynamics research highlights its diagnostic significance. Concurrently, EndoFLIP's emerging clinical relevance is evident in diagnosing and guiding the treatment of coexisting esophageal motility issues. This review integrates contemporary research to delineate the contributions of HREM, EndoFLIP, and novel technologies in GERD. It examines their efficacy in facilitating an accurate diagnosis, differentiating similar gastrointestinal disorders, quantifying the extent of reflux, assessing the severity of the disease, forecasting patient responsiveness to proton pump inhibitor therapy, and guiding decisions for surgical interventions. The overarching aim is to deepen the understanding of GERD's underlying mechanisms and advance the formulation of holistic, efficacious treatment approaches. [ABSTRACT FROM AUTHOR]

Oil Palm is a prominent and primary plantation commodity in Indonesia, with extensive and expansive plantations making traditional management methods in abnormality assessment impractical and resource intensive. This study contributes to the field by utilizing a more efficient approach using advanced technology. In an attempt to address this issue, this research utilizes a trained YOLOv5 model to perform oil palm tree counting and employs NDVI to assess their abnormalities. The result shows similar or slightly superior performance compared to previous studies, with improvement in F1 score from 0.81 to 0.83 and confusion matrix calculation showing NDVI accuracy of 72.7%. This illustrates the effectiveness of the trained YOLO model for oil palm tree counting and NDVI for oil palm tree abnormalities assessment. [ABSTRACT FROM AUTHOR]

This study on regional development investigates if digital transformation is a means to attract innovative establishments to municipalities. By doing so, the relationship between the availability of high-speed broadband close by and the number of innovative establishments (workplaces) across all 290 municipalities in Sweden is explored. Panel data for eleven years (2010-2021) originate from official registers. Results based on Fixed Effects Poisson estimations including spatially weighted variables indicate that the digital transformation in the guise of high-speed broadband access is important for ICT (micro) establishments and those in declining municipalities, although the proportion of highly skilled inhabitants renders stronger estimates. For high technology and R&D establishments, access to high-speed broadband is not a relevant location factor. The estimates are robust to endogeneity as tested by the control function approach. [ABSTRACT FROM AUTHOR]

The promotion of R&D carries the risk that economically strong regions will benefit to a greater extent and that regional disparities will increase by focusing the economy on high technology. However, this is expected to depend on the specific sectoral and technological composition of R&D funding. R&D funding for a bio-based economy in Germany is particularly illustrative for a shift in funding focus from a narrow concept of biotechnology to a broader concept of bioeconomy. Along with this shift, an impact on the spatial distribution of R&D funding is assumed. Against the background of inclusive innovation policy, this study examines the potential of the bioeconomy for a reduction of regional disparities in public R&D funding. Based on a database containing publicly-funded R&D projects in Germany and further regional data, comparative regressions are conducted in order to identify spatial patterns. The results demonstrate distinct funding mechanisms in the different areas of the bioeconomy. The broadening of R&D funding for bio-based activities from the biotechnology vision towards bioresources and bioecology leads to a greater participation of rural and lagging regions which is expected to be the result of the inclusion of more traditional industries as recipients of R&D funding. [ABSTRACT FROM AUTHOR]

The Fourth Industrial Revolution, shortly called Industry 4.0, is a technology-based paradigm characterized by fully automated and unmanned smart factories to increase productivity and efficiency in manufacturing and production environments. Although Industry 4.0 has been successful in its economic goals in the last decade, its negative effects on social and environmental sustainability have been discussed for a long time. As a result of the discussions focusing especially on the exclusion of human workforce and potential from production environments, the European Commission announced a novel approach in 2021 called Industry 5.0, with the vision of benefiting from all advanced technology for, and with humans. This new paradigm, which points out a human-centric, resilient, and sustainable European industry for the future, suggests prioritizing the needs and well-being of employees and society rather than economic concerns in the development, design, and adaptation of innovative technologies. In this study, the adaptation of the Industry 5.0 approach to supply chain management is examined on the basis of human centricity, and a framework for strategic and technological requirements is presented for a successful implementation. [ABSTRACT FROM AUTHOR]