Miracle-dz/UniFAR-FTUs huggingface dataset:
Time Dependence of Reliability of Noncontrast Computed Tomography in Comparison to Computed Tomography Angiography Source Image in Acute Ischemic Stroke

There is no consensus on how the reliability and predictive ability of noncontrast computed tomography (NCCT) and computed tomography angiography source image (CTASI) change over time from acute ischemic stroke onset. We hypothesized that the reliability for detecting early ischemic changes (EIC) would be lower in early time periods and that changes identified on CTASI would be more reliable across examiners than changes identified on NCCT. To address this, we compared the relationships between CTASI, NCCT, and final infarct in patients with initial computed tomography (CT) imaging at different time points after stroke onset. Patients with acute ischemic stroke with proximal anterior circulation occlusions (internal carotid artery, middle carotid artery M1, proximal M2) from Calgary CT Angiography (CTA) database were studied. The cohort was categorized in four groups based on time from stroke onset to baseline NCCT/CTA: 0–90 mins (n = 69), 91–180 mins (n = 88), 181–360 mins (n = 46), and >360 mins (n = 58). Median scores of NCCT-Alberta Stroke Program Early CT Score (ASPECTS), CTASI ASPECTS, and follow-up ASPECTS among different time categories were compared. To determine reliability, a subsample of NCCT brain and CTASI were interpreted at separate sessions weeks apart by two neuroradiologists and two stroke neurologists in random order. Median and mean ASPECTS ratings on NCCT and CTASI were higher than final ASPECTS in each time category (P < 0·001 for all comparisons). CTASI ASPECTS was lower than NCCT ASPECTS in each time category, and differences were significant at 0–90 mins and 91–180 mins (P < 0·001). The least agreement among readers was in detection of EIC on NCCT brain in the ultra-early phase (<90 mins) [intraclass correlation coefficient (ICC) = 0·48. By contrast, there was excellent agreement on EIC on CTASI regardless of time period (ICC = 0·87–0·96). Using ASPECTS methodology, CTASI is more reliable than NCCT at predicting final infarct extent particularly in the early time windows.
TQ-TTFS: High-Accuracy and Energy-Efficient Spiking Neural Networks Using Temporal Quantization Time-to-First-Spike Neuron

In recent years, spiking neural networks (SNNs) have gained attention for their biological realistic and event-driven characteristics, which align well with neuromorphic hardware. Time-to-First-Spike (TTFS) coding is an coding scheme for SNNs, where neurons are fired only once throughout the inference process, reducing the number of spikes and improving energy efficiency. However, the SNNs with TTFS coding face the issue of low classification accuracy. This paper introduces TQ-TTFS, a temporal quantization on TTFS neuron model to address this issue. In addition, the temporal quantization neurons can apply lower clock frequency without increasing inference latency, which can lead to higher energy efficiency. The experimental results show the effectiveness of the proposed temporal quantization neuron model in improving both classification accuracy and energy efficiency. In our simulations TQ-TTFS achieves classification accuracy of 98.6% on MNIST dataset and 90.2% on FashionMNIST dataset which are among SOTA of temporal coding SNNs. An analysis is also given to show that TQ-TTFS on an example SNN can have $2.94 \times$ energy efficiency improvement compared with tranditional TTFS coding.
On the impact of backhaul channel reliability on cooperative wireless networks

We study the effect of unreliable backhaul links on the performance of Coordinated Multi-Point (CoMP) techniques. CoMP has emerged as a powerful scheme to mitigate co-channel interference. Economically viable deployment of Heterogeneous Networks (HetNets) will require the use of lower-performance backhaul options, e.g. non-line-of-sight (NLOS) microwave links. Motivated by HetNets, a backhauling model is introduced, by assigning Link Failure Probability (LFP) to backhaul links, for the cooperative clusters. In this paper we analyze the centralized and semi-distributed CoMP architectures. We investigate the probability of deficient backhaul links reducing quality of service, by impeding transmission. By evaluating the average sum rate of users within a CoMP cluster, we show how backhaul link reliability affects the performance of the cooperative cluster. We conclude, that the performance gains offered by CoMP quickly diminish, as the unreliability of the backhaul links grows.
A CQI Feedback Reduction Scheme for Multi-User MIMO/OFDMA Systems

An opportunistic scheduling is adopted to improve the capacity of the system by exploiting the multiuser diversity of multiuser MIMO (MU-MIMO)systems. However, it requires a large amount of feedback carrying the channel quality information (CQI) of each user to the transmitter. The considered per user unitary and rate control (PU2RC) needs to feedback the preferred precoding index and its CQIs, and it has a defect in scheduling the streams for the grouped user. In order to overcome these drawbacks, a novel feedback reduction scheme is proposed and is modified for OFDMA systems in this paper. It employs transmitter controlled precoding and opportunistic feedback (TCP-OFB) in conjunction with frequency scheduling. The simulation results demonstrate that TCP-OFB/OFDMA shows comparable performance to PU2RC while it only requires far reduced feedback load.
Proposal for Enhancing Legal Advisory Services in the Montenegrin Banking Sector with Artificial Intelligence

This paper examines the integration of Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) in improving legal advisory services within the Montenegrin banking industry. It explores the vectorization of regulatory documents using ADA-2 embedding model, the storage and management of these vectorized forms in Chroma DB, and the utilization of GPT-4 for processing relevant documents to generate user responses, providing insights into the use of artificial intelligence (AI) for legal advisement and financial education.
LOCALMOR: Localized multi-objective routing for wireless sensor networks

This paper proposes a multi-objective quality of service (QoS) routing protocol for wireless sensor networks (WSN). The protocol takes into account the traffic diversity typical for many applications and provides a differentiation in routing using QoS metrics. It ensures several QoS metrics for different traffic categories, and attempts for each packet to fulfill the required metrics in a power-aware and localized way. It employs memory and computation efficient estimators in a distributed manner and uses a multi-sink single-path approach to increase reliability. The main contribution of this paper is data traffic based QoS with regard to all the considered QoS metrics. As far as we know, this protocol is the first that makes use of the diversity in the data traffic while considering latency, reliability, residual energy in the sensor nodes, and transmission power between nodes and casts QoS metrics as a multi-objective problem. The proposed algorithm can operate with any MAC protocol, provided that it employs an ACK mechanism. Simulation results show the proposed protocol outperforms all compared state-of-the-art QoS and localized routing protocols.
An alternative proof of the rate-distortionfunction of poisson processes with a queueing distortion measure.

This paper presents a proof of the rate distortion function of a Poisson process with a queuing distortion measure that is in complete analogy with the proofs associated with the rate distortion functions of a Bernoulli source with Hamming distortion measure and a Gaussian source with squared-error distortion measure. Analogous to those problems, the distortion measure that we consider is related to the logarithm of the conditional distribution relating the input to the output of a well-known channel coding problem, specifically the Anantharam and Verdu “Bits through Queues” [1] coding problem. Our proof of the converse utilizes McFadden’s point process entropy formulation [2] and involves a number of mutual information inequalities, one of which exploits the maximum-entropy achieving property of the Poisson process. Our test channel uses Burke’s theorem [3], [4] to prove achievability.
Efficient flooding using relay routing in on-demand Routing protocol for Mobile Adhoc Networks

In this paper an enhancement technique for Dynamic Source Routing protocol (DSR) using relay routing and flooding alternately is proposed. DSR is a popular on demand reactive routing protocol in Mobile Adhoc Networks (MANET) which uses flooding for route discovery and route maintenance when only a node has data to be transmitted. Flooding causes serious redundancy, contention and collision in the network which increases the overhead of transmission in a dynamic network where the nodes have different mobilities. In order to reduce this routing overhead we have used relay routing technique which selects only a small number of nodes in the neighbourhood of the source node for route discovery and route maintenance. Selection of the nodes is done based on the mobility of the neighbourhood nodes at that instant of time. Simulation results on DSR have shown that this technique can reduce redundant flooding to a great extent thus making DSR more efficient.
Human T lymphocyte cAMP‐dependent protein kinase: subcellular distributions and activity ranges of type I and type II isozymes

The role of the type I and type II protein kinase A isozymes in the regulation of human T lymphocyte immune effector functions has not been ascertained. To approach this question, we first characterized the distribution and enzyme activities of the type I and type II protein kinase A (PKA) isozymes in normal, human T lymphocytes. T cells possess both type I and type II isozymes with an activity ratio of 5.0:1 ± 0.71 (mean ± SD). The type I isozyme associates predominately with the plasma membrane whereas the type II isozyme localizes primarily to the cytosol. Analyses of isozyme activities demonstrated that T cells from approximately one‐third of 16 healthy donors exhibited significantly higher type II isozyme activities (higher type II, type IIH) than the remaining donors (lower type II, type IIL) (mean = 605 ± 75 pmol · min–1 · mg protein–1, P < 0.001). Scatchard analyses of [3H]cAMP binding in the cytosolic fraction demonstrated similar Kd values (type IIH, 1.1 × 10–7 M; type IIL, 9.0 × 10–8 M); however, the Bmax (maximal binding) of the type IIH was 400 fmol/mg protein compared to the Bmax of the type IIL of 126 fmol/mg protein. Scatchard analysis of [3H]cAMP binding to the type I isozyme associated with membrane fragments had a Kd of 5.6 × 10–8 M and a Bmax of 283 fmol/mg protein. Eadie‐Hofstee plots of type IIH and type IIL gave a Km and Vmax of 2.3 mg/ml and 1.5 nmol · mg–1 · min–1, and 2.1 mg/ml and 1.6 nmol · mg–1 · min–1, respectively. The 3.2‐fold higher maximal binding of the type II isozyme in one‐third of healthy donors may reflect a greater amount of isozyme protein. The compartmentalization of type I PKA isozyme to the plasma membrane and type II PKA isozyme to the cytosol may serve to localize the isozymes to their respective substrates in T lymphocytes. — Hasler, P.; Moore, J. J.; Kammer, G. M. Human T lymphocyte cAMP‐dependent protein kinase: subcellular distribution and activity ranges of type I and type II isozymes. FASEB J. 6: 2735‐2741; 1992.
Application of soft magnetic composites in active magnetic bearings

One of the main application areas of active magnetic bearings is turbo machinery. Such machines run at high speeds and through application of magnetic bearing bearings mechanical contact and friction between rotor and stator can be avoided. Nevertheless magnetic bearings still cause rotor losses through eddy currents and magnetic hysteresis effects. Although these losses are way smaller than those caused by friction, in vacuum they still can cause the rotor to overheat because of the severely limited cooling. This paper presents a way to address these losses by using soft magnetic composites as active material in a magnetically suspended rotor.
Flow Induced Microvascular Network Formation of Therapeutic Relevant Arteriovenous (AV) Loop-Based Constructs in Response to Ionizing Radiation

Background The arteriovenous (AV) loop model enables axial vascularization to gain a functional microcirculatory system in tissue engineering constructs in vivo. These constructs might replace surgical flaps for the treatment of complex wounds in the future. Today, free flaps are often exposed to high-dose radiation after defect coverage, according to guideline-oriented treatment plans. Vascular response of AV loop-based constructs has not been evaluated after radiation, although it is of particular importance. It is further unclear whether the interposed venous AV loop graft is crucial for the induction of angiogenesis. Material/Methods We exposed the grafted vein to a single radiation dose of 2 Gy prior to loop construction to alter intrinsic and angio-inductive properties specifically within the graft. Vessel loops were embedded in a fibrin-filled chamber for 15 days and radiation-induced effects on flow-mediated vascularization were assessed by micro-CT and two-dimensional histological analysis. Results Vessel amount was significantly impaired when an irradiated vein graft was used for AV loop construction. However, vessel growth and differentiation were still present. In contrast to vessel density, which was homogeneously diminished in constructs containing irradiated veins, vessel diameter was primarily decreased in the more peripheral regions. Conclusions Vascular luminal sprouts were significantly diminished in irradiated venous grafts, suggesting that the interposing vein constitutes a vital part of the AV loop model and is essential to initiate flow-mediate angiogenesis. These results add to the current understanding of AV loop-based neovascularization and suggest clinical implications for patients requiring combined AV loop-based tissue transfer and adjuvant radiotherapy.
Cartification: A Neighborhood Preserving Transformation for Mining High Dimensional Data

The analysis of high dimensional data comes with many intrinsic challenges. In particular, cluster structures become increasingly hard to detect when the data includes dimensions irrelevant to the individual clusters. With increasing dimensionality, distances between pairs of objects become very similar, and hence, meaningless for knowledge discovery. In this paper we propose Cartification, a new transformation to circumvent this problem. We transform each object into an item set, which represents the neighborhood of the object. We do this for multiple views on the data, resulting in multiple neighborhoods per object. This transformation enables us to preserve the essential pair wise-similarities of objects over multiple views, and hence, to improve knowledge discovery in high dimensional data. Our experiments show that frequent item set mining on the certified data outperforms competing clustering approaches on the original data space, including traditional clustering, random projections, principle component analysis, subspace clustering, and clustering ensemble.
Fostering the Intelligent Novice: Learning From Errors With Metacognitive Tutoring

This article explores 2 important aspects of metacognition: (a) how students monitor their ongoing performance to detect and correct errors and (b) how students reflect on those errors to learn from them. Although many instructional theories have advocated providing students with immediate feedback on errors, some researchers have argued that immediate feedback eliminates the opportunity for students to practice monitoring for and learning from errors. Thus, they advocate delayed feedback. This article provides evidence that this line of reason is flawed and suggests that rather than focusing on the timing of feedback, instructional designers should focus on the "model of desired performance" with respect to which feedback is provided. Instead of delaying feedback, we suggest broadening our model of correct behavior or desired performance to include some kinds of incorrect, but reasonable behaviors. This article explores the effects of providing feedback on the basis of a so-called intelligent novice cognitive model. A system based on an intelligent novice model allows students to make certain reasonable errors, and provides guidance through the exercise of error detection and correction skills. There are two pedagogical motivations for feedback based on an intelligent novice model. First, jobs today not only require ready-made expertise for dealing with known problems, but also intelligence to address novel situation where nominal experts are thrown back to the state of a novice. Second, the opportunity to reason about the causes and consequences of errors may allow students to form a better model of the behavior of domain operators. Results show that students receiving intelligent novice feedback acquire a deeper conceptual understanding of domain principles and demonstrate better transfer and retention of skills over time.
Query polyrepresentation for ranking retrieval systems without relevance judgments

Ranking information retrieval (IR) systems with respect to their effectiveness is a crucial operation during IR evaluation, as well as during data fusion. This paper offers a novel method of approaching the system ranking problem, based on the widely studied idea of polyrepresentation. The principle of polyrepresentation suggests that a single information need can be represented by many query articulations–what we call query aspects. By skimming the top k (where k is small) documents retrieved by a single system for multiple query aspects, we collect a set of documents that are likely to be relevant to a given test topic. Labeling these skimmed documents as putatively relevant lets us build pseudo-relevance judgments without undue human intervention. We report experiments where using these pseudo-relevance judgments delivers a rank ordering of IR systems that correlates highly with rankings based on human relevance judgments.
First Passage Percolation on the Erdős–Rényi Random Graph

In this paper we explore first passage percolation (FPP) on the Erdős–Rényi random graph Gn(pn), where we assign independent random weights, having an exponential distribution with rate 1, to the edges. In the sparse regime, i.e., when npn → λ > 1, we find refined asymptotics both for the minimal weight of the path between uniformly chosen vertices in the giant component, as well as for the hopcount (i.e., the number of edges) on this minimal weight path. More precisely, we prove a central limit theorem for the hopcount, with asymptotic mean and variance both equal to (λ log n)/(λ − 1). Furthermore, we prove that the minimal weight centred by (log n)/(λ − 1) converges in distribution. We also investigate the dense regime, where npn → ∞. We find that although the base graph is ultra-small (meaning that graph distances between uniformly chosen vertices are o(log n)), attaching random edge weights changes the geometry of the network completely. Indeed, the hopcount Hn satisfies the universality property that whatever the value of pn, Hn/log n → 1 in probability and, more precisely, (Hn − βn log n)/, where βn = λn/(λn − 1), has a limiting standard normal distribution. The constant βn can be replaced by 1 precisely when λn ≫ , a case that has appeared in the literature (under stronger conditions on λn) in [4, 13]. We also find lower bounds for the maximum, over all pairs of vertices, of the optimal weight and hopcount. This paper continues the investigation of FPP initiated in [4] and [5]. Compared to the setting on the configuration model studied in [5], the proofs presented here are much simpler due to a direct relation between FPP on the Erdős–Rényi random graph and thinned continuous-time branching processes.
V2V Charging and Solar Integration to Overcome Range Anxiety in Electric Vehicles

The widespread adoption of electric vehicles (EVs) grapples with a significant challenge known as ‘range anxiety’, which is the fear of depleting the battery charge before reaching the destination. This paper proposes an inventive strategy to mitigate range anxiety by integrating Vehicle-to-Vehicle (V2V) charging as a fundamental component of the EV ecosystem. The V2V charging mechanism harnesses the energy-sharing capabilities of EVs, facilitating power exchange between vehicles on the road. Our research targets the integration of solar panels onto the source vehicle, serving as a renewable energy source for V2V charging. The discussion commences by addressing the current state of range anxiety and the constraints of traditional EV charging infrastructure. The paper elucidates the design and implementation of a solar panel system on the source vehicle, emphasizing its efficiency and energy generation potential. To validate our claims, simulation results conducted in the MATLAB/Simulink environment are presented, offering a comprehensive analysis of the proposed V2V charging system's effectiveness. This paper significantly contributes to the growing body of knowledge surrounding innovative solutions for the EV industry. It underscores the potential of V2V charging, in tandem with solar panels, as a promising stride towards a more sustainable and range-anxiety-free future for electric vehicle users. The primary targets of this paper encompass elucidating V2V charging, detailing solar integration, conducting simulations, and analyzing results to provide valuable insights for the advancement of electric vehicle technology.
High‐T and low‐P metamorphism in the Xilingol Complex of central Inner Mongolia, China: An indicator of extension in a previous orogeny

The Xilingol Complex comprises biotite gneisses and amphibolite interlayers with extensive migmatization. Four representative samples were documented and found to record either two or three metamorphic stages. Phase modelling using thermocalc suggests that the observed assemblages represent the final stages that underwent cooling from temperature peaks, and are consistent with a fluid‐absent solidus in P–T pseudosections. Their P–T conditions are further constrained to be 5–6 kbar/680–725°C and 4–5 kbar/650–680°C for two garnet‐bearing gneiss samples, 4–5 kbar/660–730°C for a cordierite‐bearing gneiss sample, and 4–5 kbar/680–710°C for an amphibolite sample based on mineral composition isopleths, involving measured Mg content in biotite, anorthite in plagioclase, grossular and pyrope in garnet and Ti content in amphibole. The peak temperature conditions recovered are 760–790°C or >760°C at 5–6 kbar based on the composition isopleths of plagioclase, biotite, garnet and especially the comparison of melt contents between the calculated and observed. A pre‐peak heating process with slight decompression can be suggested for some samples on the basis of the core–rim increase in the plagioclase anorthite, and the stability of ilmenite. Zircon U–Pb dating using the LA‐ICP‐MS method provides systemic constraints on the metamorphic ages of the Xilingol Complex to be 348–305 Ma, interpreted to represent the post‐peak cooling stages. Moreover, metagabbroic dykes that intruded into the Xilingol Complex yield 317 ± 3 Ma from magmatic zircon, and are considered to have played a significant role for heat advection triggering the high‐T and low‐P metamorphism. Thus, the clockwise P–T paths involving pre‐peak heating, peak and post‐peak cooling recovered for the Xilingol Complex are consistent with an extensional setting in the Carboniferous that developed on a previous orogen in response to addition of mantle‐derived materials probably together with upwelling of the asthenospheric mantle.