Miracle-dz/UniFAR-FTUs huggingface dataset:
Artificial Intelligence in Contemporary Societies: Legal Status and Definition, Implementation in Public Sector across Various Countries

The article aims to provide a comparative analysis of determining the legal status of artificial intelligence, as well as strategic planning of its implementation in the public sector in the countries of the Romano-Germanic, Anglo-Saxon, socialist, religious, and traditional systems of law. The study replies to the research questions regarding statutory definition of AI, state authorities responsible for AI, national government strategy in the field of AI and targets set therein, and action plans of AI with reference to countries with the highest Global Talent Competitiveness Index in reference to the mentioned legal systems. The research is of qualitative and applied nature; theoretical analysis of academic sources provides the groundwork for ICT-facilitated thematic content analysis of legal and administrative documents of the mentioned countries. The findings reveal common and specific trends regarding the data under study, and allow the author to suggest a revision of AI definition and to specify legislative and doctrinal issues that seem to be relevant and promising in the further strategic development and implementation of AI in the public sphere across countries.
Estimation on LN2 Level and Condensation of Insulation Gas in HTS Power Cable Termination

The terminations of high-temperature superconducting (HTS) power cables help supply current between the cryogenic HTS power cable and the room temperature power system while maintaining electrical insulation. This involves a cryogenic section with circulating liquid nitrogen (LN2) for cooling the HTS power cable and temperature gradient section with level interface formed by thermal equilibrium and an ambient section with current leads and insulation gases such as nitrogen and sulfur hexafluoride (SF6). The level of LN2 varies depending on the structure of the termination and the operation conditions, and this may further affect the temperature of the ambient section that is installed at the upper end of the cryogenic section. As the level of LN2 increases, the temperature of the insulation gas decreases and condenses, resulting in a significant decrease in the dielectric strength. Therefore, it is crucial to estimate the level of LN2 while designing the termination for HTS power cable. In this study, the LN2 level of the termination was estimated according to heat load and the operating conditions to avoid dielectric breakdown of insulation gas are proposed using a commercial thermo-fluid network analysis tool, SINDA/FLUINT.
State Feedback H_∞Control for a Class of Nonlinear Stochastic Systems

This paper discusses the H_∞control problem for a class of nonlinear stochastic systems driven by Brownian motion with both the control and exogenous disturbance entering the diffusion.By an inequality of quadric form,an approach to solving Hamilton-Jacobi equations(HJEs,for short)with parameters is presented,and both infinite and finite horizon nonlinear stochastic H_∞designs are also developed.Finally,we discuss the solvability of such HJEs with parameters.
What Problem Should Skills Solve? Interrogating Theories of Change Underpinning Strategies and Interventions in Vocational Education and Skills in LMICs

The aim of this paper is to understand the ‘theory of change’ underlying interventions to support vocationalisation of general education as well as vocational education and training (VET) and skills development. The focus is on interventions supported by development agencies and donors, although national policies are also considered, as the agencies work with governments and are both guided by, and influence, their priorities. The first aim is to interrogate what problem VET is seen as the answer to, and how VET is seen to solve that problem (their theory of change). The second aim is to understand the extent to which, and ways in which, vocationalising education is supported and VET favoured, as compared to other components of the education system such as early childhood development, early primary education, or university expansion, as an educational intervention. We found that while some organisations have explicit theories of change—generally multiple theories of change addressing different aspects of the overarching system—many are currently in the process of developing these theories of change. A few state that they do not have a theory of change but rather focus on the development of targets for different components of the system.
High isolation and high power of 0.13 µm CMOS SPDT switch using deep‐N‐well transistors and floating‐body technique in K‐band

A K‐band high isolation single‐pole double‐throw (SPDT) switch using a 0.13 µm CMOS process is presented. Two on‐state resistors of shunt Deep‐N‐Well (DNW) transistors are used to improve isolation. The floating‐body technique is utilized to enhance the power‐handling capability. The off‐state capacitors of two DNW transistors are employed to construct an impedance‐matching network. The switch achieves a measured insertion loss of 3.0–3.2 dB and an isolation of better than 35 dB from 17 to 27 GHz. A measured input 1 dB compression power (IP1dB) of 11.8 dBm is obtained at 24 GHz. The chip size of the proposed switch is 0.52 × 0.66 mm2 with a core area of only 0.33 × 0.27 mm2.
Resonant enhanced low-power nonlinear tuning capability using an As2S3 waveguide on LiNbO3

In this work, we present fabrication and measurement results of an As2S3-on-LiNbO3 ring resonator waveguide and sidewall grating cavity waveguide. The nonlinear tuning capability is demonstrated on a fabricated ring resonator waveguide by injecting the signal-pump optical power into the device and observing the nonlinear phase shift. The nonlinear tunability of our hybrid As2S3-on-LiNbO3 grating cavity waveguide is numerically analyzed.
Gradient descent technology for sparse vector learning in ontology algorithms

Abstract In the information retrieval field, ontology plays a crucial role in searching for information that is highly semantic similar to the query concept in origin. It also plays a major roles in returning the results to the user. The main purpose of ontology algorithm lies in obtaining the function for calculating the similarity between concepts. One learning technology in applying ontology is to obtain a ontology function f:V Æ R In this structure, it maps each vertex to a real number and the similarity between two concepts is then determined by the difference of their real numbers. In this article, we report a sparse vector learning algorithm for ontology similarity measure and ontology mapping in terms of gradient descent and iterative computation. The ontology penalty term in optimization model is reformulated by virtue of dual norm, and then the smooth approximation to this penalty term is obtained. The main procedure of our algorithm is iterative computation based on gradient descent tricks. Results achieved in the simulation experiments show that the new proposed algorithm is highly efficient and accuracy in ontology similarity measure and ontology mapping in multiple disciplines.
Cross-View Image Synthesis From a Single Image With Progressive Parallel GAN

Cross-view image synthesis aims to synthesize a ground-view image covering the same geographic region for a given single aerial-view image (or vice versa). Existing approaches typically tackle this challenging task by relaxing the single-image constraint and using a ground-truth semantic map as additional input to aid synthesis. However, this is nearly infeasible in practice. In this article, we investigate how to generate a detail-enriched and structurally accurate ground-level image from only a single aerial-level input image, without any other prior knowledge except for the input image. Toward this goal, we propose a novel progressive parallel generative adversarial network (PPGAN) that starts by generating low-resolution outputs and progressively produces ground images at higher resolutions as the network propagates forward. In this manner, our PPGAN decomposes the task into several manageable sub-tasks, which helps generate detail-enriched and structurally accurate ground images. During progressive generation, the PPGAN uses a parallel generation paradigm that enables the generator to produce multiresolution images in parallel, thereby avoiding excessive time cost on training. Furthermore, for effective information propagation across multiresolution images, a feature fusion module (FFM) is devised to mitigate the domain gap between cross-level image features, which enables a balance of detail and structural information synthesis. In addition, the proposed channel-space attention selection module (CSASM) learns the mapping relationship between cross-view images in a larger scale space to enhance the quality of the output image. Quantitative and qualitative experiments demonstrate that our method requires only one input image without the aid of additional inputs, but is capable of synthesizing detail-enriched and structurally accurate ground images and outperforms the existing state-of-the-art methods on two famous benchmarks.
Deletion of Cryab increases the vulnerability of mice to the addiction-like effects of the cannabinoid JWH-018 via upregulation of striatal NF-κB expression

Synthetic cannabinoids have exhibited unpredictable abuse liabilities, especially self-administration (SA) responses in normal rodent models, despite seemingly inducing addiction-like effects in humans. Thus, an efficient pre-clinical model must be developed to determine cannabinoid abuse potential in animals and describe the mechanism that may mediate cannabinoid sensitivity. The Cryab knockout (KO) mice were recently discovered to be potentially sensitive to the addictive effects of psychoactive drugs. Herein, we examined the responses of Cryab KO mice to JWH-018 using SA, conditioned place preference, and electroencephalography. Additionally, the effects of repeated JWH-018 exposure on endocannabinoid- and dopamine-related genes in various addiction-associated brain regions were examined, along with protein expressions involving neuroinflammation and synaptic plasticity. Cryab KO mice exhibited greater cannabinoid-induced SA responses and place preference, along with divergent gamma wave alterations, compared to wild-type (WT) mice, implying their higher sensitivity to cannabinoids. Endocannabinoid- or dopamine-related mRNA expressions and accumbal dopamine concentrations after repeated JWH-018 exposure were not significantly different between the WT and Cryab KO mice. Further analyses revealed that repeated JWH-018 administration led to possibly greater neuroinflammation in Cryab KO mice, which may arise from upregulated NF-κB, accompanied by higher expressions of synaptic plasticity markers, which might have contributed to the development of cannabinoid addiction-related behavior in Cryab KO mice. These findings signify that increased neuroinflammation via NF-κB may mediate the enhanced addiction-like responses of Cryab KO mice to cannabinoids. Altogether, Cryab KO mice may be a potential model for cannabinoid abuse susceptibility.
Physiological effects of in ovo delivery of bioactive substances in broiler chickens

The poultry industry has improved genetics, nutrition, and management practices, resulting in fast-growing chickens; however, disturbances during embryonic development may affect the entire production cycle and cause irreversible losses to broiler chicken producers. The most crucial time in the chicks' development appears to be the perinatal period, which encompasses the last few days of pre-hatch and the first few days of post-hatch. During this critical period, intestinal development occurs rapidly, and the chicks undergo a metabolic and physiological shift from the utilization of egg nutrients to exogenous feed. However, the nutrient reserve of the egg yolk may not be enough to sustain the late stage of embryonic development and provide energy for the hatching process. In addition, modern hatchery practices cause a delay in access to feed immediately post-hatch, and this can potentially affect the intestinal microbiome, health, development, and growth of the chickens. Development of the in ovo technology allowing for the delivery of bioactive substances into chicken embryos during their development represents a way to accommodate the perinatal period, late embryo development, and post-hatch growth. Many bioactive substances have been delivered through the in ovo technology, including carbohydrates, amino acids, hormones, prebiotics, probiotics and synbiotics, antibodies, immunostimulants, minerals, and microorganisms with a variety of physiological effects. In this review, we focused on the physiological effects of the in ovo delivery of these substances, including their effects on embryo development, gastrointestinal tract function and health, nutrient digestion, immune system development and function, bone development, overall growth performance, muscle development and meat quality, gastrointestinal tract microbiota development, heat stress response, pathogens exclusion, and birds metabolism, as well as transcriptome and proteome. We believe that this method is widely underestimated and underused by the poultry industry.
Multidisciplinary Approach to Spinal Metastases and Metastatic Spinal Cord Compression—A New Integrative Flowchart for Patient Management

Simple Summary The prevalence of metastatic spine disease is progressively increasing, affecting a growing group of heterogeneous and complex patients. A multidisciplinary, personalized approach, enriched by the expertise of each involved specialty (namely oncologists, radiotherapists, neurosurgeons, orthopedic surgeons, hematologists, and neuroradiologists), is pivotal and achieves superior results in terms of clinical outcomes. We reviewed the most recent data regarding the pathophysiology of metastatic spine disease, prognostic scores, and available treatment options and formulated a proposal for an updated algorithmic approach to the pathology according to the clinical scenario of each patient. A flowchart-based approach to patients offers an evidence-based management of metastatic spine disease, providing a valuable clinical decision tool in a context of high uncertainty and quick-acting need. Nevertheless, we underline that the goal of this type of approach is to assist in clinical decisions, not to replace a case-by-case reflection concerning the specificities of each patient. Abstract Metastatic spine disease (MSD) and metastatic spinal cord compression (MSCC) are major causes of permanent neurological damage and long-term disability for cancer patients. The development of MSD is pathophysiologically framed by a cooperative interaction between general mechanisms of bone growth and specific mechanisms of spinal metastases (SM) expansion. SM most commonly affects the thoracic spine, even though multiple segments may be affected concomitantly. The great majority of SM are extradural, while intradural-extramedullary and intramedullary metastases are less frequently seen. The management of patients with SM is particularly complex and challenging, with multiple factors—such as the spinal stability status, primary tumor radio and chemosensitivity, cancer biological burden, patient performance status and comorbidities, and patient’s oncological prognosis—influencing the clinical decision-making process. Different frameworks were developed in order to systematize and support this process. A multidisciplinary, personalized approach, enriched by the expertise of each involved specialty, is crucial. We reviewed the most recent evidence and proposed an updated algorithmic approach to patients with MSD according to the clinical scenario of each patient. A flowchart-based approach offers an evidence-based management of MSD, providing a valuable clinical decision tool in a context of high uncertainty and quick-acting need.
Change in extreme precipitation events: Exposure and vulnerability in the Poyang Lake Basin, China

On the basis of daily observations data from 1984 to 2020, the spatiotemporal characteristics of extreme precipitation events in the Poyang Lake Basin (China) were analyzed using the intensity–area–duration method. With consideration of spatially distributed data on gross domestic product (GDP), population, and disaster losses related to historical extreme precipitation events, the exposure and vulnerability of the population and GDP of the study area to extreme precipitation events were systematically assessed. The results revealed the following. 1) The intensity and frequency of extreme precipitation, as well as the area affected, showed trends of increase, especially in the northeast of the basin. 2) Population exposure in the basin showed a trend of increase of 2.43 million/a. Change in population exposure was greatest in the most recent 10 years, with an average increase of 6.64 million/a. Change in extreme precipitation was the primary driver of the rapid increase in population exposure. 3) The average annual GDP exposure of the basin was ¥5.43 billion, and economic exposure has increased substantially at an average rate of ¥0.56 billion/a. Unlike population exposure, the increase in economic exposure was driven mainly by rapid economic growth. 4) By constructing vulnerability curves of economic losses in different decades, the trend of economic vulnerability was found to have clearly declined, i.e., economic vulnerability in 2010 was 13.3 (4.1) times lower than that in the 1990s (2000s). Effective disaster prevention and reduction measures should urgently be adopted in the study area to mitigate the effects of increase in extreme precipitation events.
Future of Artificial Intelligence Applications in Cancer Care: A Global Cross-Sectional Survey of Researchers

Cancer significantly contributes to global mortality, with 9.3 million annual deaths. To alleviate this burden, the utilization of artificial intelligence (AI) applications has been proposed in various domains of oncology. However, the potential applications of AI and the barriers to its widespread adoption remain unclear. This study aimed to address this gap by conducting a cross-sectional, global, web-based survey of over 1000 AI and cancer researchers. The results indicated that most respondents believed AI would positively impact cancer grading and classification, follow-up services, and diagnostic accuracy. Despite these benefits, several limitations were identified, including difficulties incorporating AI into clinical practice and the lack of standardization in cancer health data. These limitations pose significant challenges, particularly regarding testing, validation, certification, and auditing AI algorithms and systems. The results of this study provide valuable insights for informed decision-making for stakeholders involved in AI and cancer research and development, including individual researchers and research funding agencies.
Design and Commissioning of a Dual Visible/Near-IR Echelle Spectrograph for the AEOS Telescope

The Institute for Astronomy has developed and recently installed a high-resolution cross-dispersed echelle spectrograph for use at one of the coudé foci of the AEOS 3.7-meter telescope, operated by the Air Force Space Command atop Mt. Haleakala on the island of Maui. The spectrograph features an optical arm for the wavelength range 0.5 - 1.0 μm and an infrared arm for the range 1.0 - 2.5 μm. We review the spectrograph design and present commissioning results obtained with both the visible and infrared arms. Both channels use a white-pupil collimator design to maximize grating efficiency and to limit the size of the camera optics. The visible arm of the spectrograph uses deep-depletion CCDs optimized for operation near 1.0 μm. The infrared detector is a 2048 x 2048 HgCdTe array (HAWAII-2) that has been developed by the Rockwell Science Center for this project. Both channels are equipped with slit-viewing cameras for object acquisition and control of a fast guiding tip-tilt mirror located at a pupil image in the spectrograph fore optics.
Point Process and Partial Sum Convergence for Weakly Dependent Random Variables with Infinite Variance

Let {ξ j } be a strictly stationary sequence of random variables with regularly varying tail probabilities. We consider, via point process methods, weak convergence of the partial sums, S n = ξ 1 +. + ξ n , suitably normalized, when {ξ j } satisfies a mild mixing condition. We first give a characterization of the limit point processes for the sequence of point processes N n with mass at the points {ξ j /a n , j = 1 n}, where a n is the 1 - n -1 quantile of the distribution of |ξ 1 |. Then for 0 t n ] →0, P[S n > t n ]/(nP[ξ 1 > t n ]) tends to a constant which can in general be different from 1. Applications of our main results to self-norming sums, m-dependent sequences and linear processes are also given.
Drivers and Potential Consequences of Observed Extreme Hypoxia Along the Canadian Pacific Continental Shelf

Bottom waters of the northeast Pacific continental shelf naturally experience localized hypoxic conditions, with significant influences on food webs and biogeochemical cycling. In August 2021, extreme hypoxia was detected from several measurement platforms along the southern British Columbia continental shelf, with oxygen concentration <60 μmol kg−1, and a difference from the seasonal climatology of more than 2 standard deviations. Early and intense remote upwelling and local density shifts were associated with an anomalously strong spring phytoplankton bloom, which likely stimulated localized respiration of subsurface organic matter. This event was concurrent with unsuitable habitat for Pacific halibut and calcite and aragonite undersaturation throughout most of the water column. The drivers of this extreme low oxygen event could be enhanced under future climate change, with potentially significant impacts on marine ecology and biogeochemistry.
Load Current Control of One Pulsewidth Modulation for Dynamic Wireless Power Transfer System Using Vehicular AC Current Estimation

A wireless power transfer (WPT) system has been considered applicable to various charging applications. Dynamic WPT technology for electric vehicles limits communication speed and capacity due to the separation of assemblies between the ground and vehicle sides. It is challenging to communicate signals synchronized with the transmission frequency at the same timing. Hence, the system that controls the power only by the vehicle itself is necessary for the sake of safety. This article proposes a dynamic WPT system in which only the vehicle-side assembly acquires a synchronized signal and controls the load current to the battery. The theoretical analysis concludes that an input voltage derives an output ac current as a constant, and the one-pulsewidth modulation for a converter changes a load current. A feed-forward control method of its current estimation is proposed. The bench system is designed, constructed, and tested to verify the effectiveness of the proposed method compared with the proportional–integral control in a static state. Furthermore, the system is also verified when in motion. The load current was limited to the maximum value of the system in areas where the coupling coefficient is high, while the current value was well controlled in the other areas.