Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantifying reduction in ecological risk in Penrhyn Estuary, Sydney, Australia, following groundwater remediation

The environmental risk associated with discharge of contaminated groundwater containing a complex mixture of at least 14 volatile chlorinated hydrocarbons (VCHs) to Penrhyn Estuary, Sydney, Australia has previously been assessed. That probabilistic ecological risk assessment (ERA) was undertaken using surface water monitoring data from 2004 to 2005. Subsequently, in 2006, a groundwater remediation system was installed and commissioned to prevent further discharge of VCHs into the estuary. The present study assessed the ecological risk posed to the estuary after 2006 to evaluate the success of the remediation system. The ERA was undertaken using toxicity data derived from direct toxicity assessment (DTA) of preremediation contaminated groundwater using indigenous species, exposure data from surface water monitoring between 2007 and 2008 and the joint probability curve (JPC) methodology. The risk posed was measured in 4 zones of the entire site: source area (2), tributary (2), the inner estuary and outer estuary at high, low, and a combination of high and low tides. In the 2 source areas, risk decreased by over 2 and over 1 orders of magnitude to maximum values of less than 0.5%. In 1 estuary, risk decreased by over 1 order of magnitude, from a maximum of 36% to a maximum of 2.3%. At the other tributary and both the inner and outer estuaries, the risk decreased to less than 1%, regardless of the tide. This analysis revealed that the remediation system was very effective and that the standard level of protection required for slightly to moderately affected ecosystems (95% of species) by the Australian and New Zealand Guidelines for Fresh and Marine Water Quality was met postremediation. Integr Environ Assess Manag 2012;8:98–106. © 2011 SETAC
P53 Family Members Modulate the Expression of PRODH, but Not PRODH2, via Intronic p53 Response Elements

The tumor suppressor p53 was previously shown to markedly up-regulate the expression of the PRODH gene, encoding the proline dehydrogenase (PRODH) enzyme, which catalyzes the first step in proline degradation. Also PRODH2, which degrades 4-hydroxy-L-proline, a product of protein (e.g. collagen) catabolism, was recently described as a p53 target. Here, we confirmed p53-dependent induction of endogenous PRODH in response to genotoxic damage in cell lines of different histological origin. We established that over-expression of TAp73β or TAp63β is sufficient to induce PRODH expression in p53-null cells and that PRODH expression parallels the modulation of endogenous p73 by genotoxic drugs in several cell lines. The p53, p63, and p73-dependent transcriptional activation was linked to specific intronic response elements (REs), among those predicted by bioinformatics tools and experimentally validated by a yeast-based transactivation assay. p53 occupancy measurements were validated in HCT116 and MCF7 human cell lines. Conversely, PRODH2 was not responsive to p63 nor p73 and, at best, could be considered a weak p53 target. In fact, minimal levels of PRODH2 transcript induction by genotoxic stress was observed exclusively in one of four p53 wild-type cell lines tested. Consistently, all predicted p53 REs in PRODH2 were poor matches to the p53 RE consensus and showed very weak responsiveness, only to p53, in the functional assay. Taken together, our results highlight that PRODH, but not PRODH2, expression is under the control of p53 family members, specifically p53 and p73. This supports a deeper link between proteins of the p53-family and metabolic pathways, as PRODH modulates the balance of proline and glutamate levels and those of their derivative alpha-keto-glutarate (α-KG) under normal and pathological (tumor) conditions.
Research on Finite Element-Based Zero-Value Insulator String Heating Identification Technology

To investigate the thermal distribution characteristics in insulator strings incorporating zero-value insulators, this study selects seven XP-70 type suspended disc insulator strings as the focal subjects. A sophisticated finite element simulation was employed to develop a coupled electric-thermal multiphysics model, aimed at examining how zero-value insulators influence the electrical potential and thermal distribution across various segments of the insulator strings. The findings reveal that standard insulator strings exhibit a relatively narrow temperature fluctuation range, whereas those with zero-value insulators demonstrate a significantly wider range. The study also observed that the placement of zero-value insulators variably impacts the thermal distribution along the strings, yet consistently proves effective in their identification. Importantly, this research substantiates the feasibility of employing infrared thermal imaging for detecting zero-value insulators, offering vital theoretical backing for such detection methods and enhancing the reliability of infrared-based diagnostics in this context.
An Architecture for Distributed Spatial Configuration of Context Aware Applications

This paper discusses an architecture for spatially distributed storage of contextual configuration information in ubiquitous computing environments. Based on the assumption that we want to integrate arbitrary mobile clients in ubiquitous computing environments, we derive the requirements for the spatial distribution of data, transparent access to context aware configuration data, and separation of context estimation algorithms. We developed a highly distributed architecture that fulfills these requirements. Using DWARF, we implemented and successfully demonstrated a mobile demonstration setup that incorporates all key concepts of our architecture. CR Categories: H.5. 1 [Information Interfaces and Presentation]: Multimedia Information Systems—Artificial, augmented, and virtual realities; C.2. 4 [Computer-Communication Networks]: Distributed Systems—Distributed applications
Processing of Idiopathic Pulmonary Fibrosis images based on spatial interpolation using DFT, FFT, DCT and LPF

The work focuses on the study of existing issues with some medical images obtained from patients with Idiopathic Pulmonary Fibrosis (IPF) who have survived this COVID-19 pandemic. This study analyzes potential causes of incorrect medical diagnoses with this disease. In this regard, we employ numerical algorithms such as DFT (Discrete Fourier Transform), FFT (Fast Fourier Transform), DCT (Discrete Cosine Transform), and LPF (Low-pass filter). The main objective of this work is to demonstrate that with these numerical algorithms based on Continuous and Discrete Fourier Theory, it is possible to filter existing noise in IPF radiography images. Furthermore, it is possible to compress, enhance, and improve their resolution so that better decisions can be made in a medical protocol. In this way, it contributes to the understanding of the true images that would be used for an optimal medical diagnosis.
Responses to toxicants of an Escherichia coli strain carrying a uspA'::lux genetic fusion and an E. coli strain carrying a grpE'::lux fusion are similar

A transcriptional fusion of the Escherichia coli uspA promoter to luxCDABE was characterized and compared with a heat shock-responsive grpE'::lux fusion. Similarities in range and rank order of inducing conditions were observed; however, the magnitude of induction was typically greater for the grpE'::lux fusion strain.
Bootstrap Partial Linear Quantile Regression and Confidence Bands ∗

In this paper uniform confidence bands are constructed for nonparametric quantile estimates of regression functions. The method is based on the bootstrap, where resampling is done from a suitably estimated empirical density function (edf) for residuals. It is known that the approximation error for the uniform confidence band by the asymptotic Gumbel distribution is logarithmically slow. It is proved that the bootstrap approximation provides a substantial improvement. The case of multidimensional and discrete regressor variables is dealt with using a partial linear model. Comparison to the classic asymptotic uniform bands is presented through a simulation study. An economic application considers the labour market discrimination effect w.r. t. different education levels.
A Model-Based Lumped Parameter Thermal Network for Online Temperature Estimation of IPMSM in Automotive Applications

Permanent magnet synchronous machines (PMSM) are widely used in industrial and automotive systems. The thermal behavior of motor parts impacts the performance of electrical drive systems, and accurate temperature information is vital for system protection and controllability. Replacing temperature sensors with thermal estimation reduces the system cost and improves the system's robustness and reliability. However, due to the complexity of high-fidelity thermal models, real-time estimation algorithms are computationally burdensome. To mitigate this computational burden, this study utilizes the calibratable and scalable 11-node reduced-order lumped-parameter thermal network (LPTN) to estimate critical PMSM temperatures in real-time. The Romer Douglas-Peucker (RDP) method is used in this study to develop surrogate loss models for interior permanent magnet machines (IPMSM). The proposed model can be applied to both transient and steady-state operational conditions. However, the temperature is obtained from averaged power loss calculations over a pre-defined raster rate. MATLAB/Simulink is used to understand the behavior of proposed reduced-order LPTN, which are compared with Motor CAD FEA results and Dyne test results to understand the accuracy of proposed models.
Exploiting an IoT local middleware for the orchestration of mobile device sensors to detect outdoor and indoor user positioning

Thanks to the proliferation of mobile technologies that enable devices to use the network for providing (publish) or requiring (subscribe) information according to specific applications aims, the Internet of Things (IoT) can be considered as the biggest challenge that the industry is currently facing. During the last years several application domains for IoT have emerged and among these the Smart Cities. In effect, the IoT is redrawing the Smart Cities in a promising way from the technological, economic, and social perspectives. This represents the background of the work described in the present paper that deals with an Ambient Assisted Living (AAL) mobile system able to detect outdoor and indoor user positioning, acquiring data through sensors in an unobtrusive way. Our system exploits an IoT middleware, called WoX (Web of Topics) and its local counterpart L-WoX (Local-Web of Topics). Thanks to its model-driven approach, it is able to allow the communication between mobile applications and a set of heterogeneous sensors, orchestrating access services and communication protocols in a very abstract way.
A Tomlinson-Harashima precoding for correlated MIMO channels

Highly correlated Multiple-Input Multiple-Output (MIMO) channels induce severe ill-conditioned MIMO channel matrices. MIMO receivers suffer from performance degradation due to the noise enhancement caused by the severe channel matrices. Precoding schemes, such as spatial Tomlinson-Harashima precoding (THP), can mitigate the performance degradation; however, the effect upon the highly correlated channels is insufficient. One way to avoid the noise enhancement is to turn off a few substreams related to the poor MIMO channels, which becomes possible by introducing an appropriate permutation matrix. We formulate a bit rate on the zero-forcing THP (ZF-THP) MIMO system, which shows that there is an optimum permutation matrix which maximizes the bit rate. We propose to apply a modified version of the sorted decomposition (SQRD) algorithm, which was originally developed for Vertical Bell Labs Layered Space Time (V-BLAST) receiver to carry out the QR decomposition of a MIMO channel matrix with permutation in its column direction simultaneously, to find a feasible permutation and create a precoder. Finally, it results in developing an efficient scheme to turn off the substreams. The proposed scheme is evaluated by computer simulations to verify its efficiency upon the correlated MIMO channels.
Using Linear Programming for Bayesian Exploration in Markov Decision Processes

A key problem in reinforcement learning is finding a good balance between the need to explore the environment and the need to gain rewards by exploiting existing knowledge. Much research has been devoted to this topic, and many of the proposed methods are aimed simply at ensuring that enough samples are gathered to estimate well the value function. In contrast, [Bellman and Kalaba, 1959] proposed constructing a representation in which the states of the original system are paired with knowledge about the current model. Hence, knowledge about the possible Markov models of the environment is represented and maintained explicitly. Unfortunately, this approach is intractable except for bandit problems (where it gives rise to Gittins indices, an optimal exploration method). In this paper, we explore ideas for making this method computationally tractable. We maintain a model of the environment as a Markov Decision Process. We sample finite-length trajectories from the infinite tree using ideas based on sparse sampling. Finding the values of the nodes of this sparse subtree can then be expressed as an optimization problem, which we solve using Linear Programming. We illustrate this approach on a few domains and compare it with other exploration algorithms.
Finite-element modelling and preliminary validation of microneedle-based electrodes for enhanced tissue electroporation

This paper investigates the use of microneedle-based electrodes for enhanced testis electroporation, with specific application to the production of transgenic mice. During the design phase, finite-element software has been used to construct a tissue model and to compare the relative performance of electrodes employing a) conventional flat plates, b) microneedle arrays, and c) invasive needles. Results indicate that microneedle-based electrodes can achieve internal tissue field strengths which are an order of magnitude higher than those generated using conventional flat electrodes, and which are comparable to fields produced using invasive needles. Using a double-sided etching process, conductive microneedle arrays were then fabricated and used in prototype electrodes. In a series of mouse model experiments involving injection of a DNA vector expressing Green Fluorescent Protein (GFP), the performance of flat and microneedle electrodes was compared by measuring GFP expression after electroporation. The main finding, supported by experimental and simulated data, is that use of microneedle-based electrodes significantly enhanced electroporation of testis.
Optimization of direct cortical stimulation using tibial versus median nerve sensory mapping during midline brain tumor resection: illustrative case

BACKGROUND During brain tumor resection, neurophysiological mapping and monitoring help surgeons locate, characterize, and functionally assess eloquent brain areas in real time. The selection of mapping and monitoring targets has implications for successful surgery. Here, the authors compare direct cortical stimulation (DCS) as suggested by median nerve (MN) with posterior tibial nerve (PTN) cortical sensory mapping (SM) during mesial lesion resection. OBSERVATIONS Recordings from a 6-contact cortical strip served to generate an MN and a PTN sensory map, which indicated the strip was anterior to the central sulcus. Responses exhibited an amplitude gradient with no phase reversal (PR). DCS, elicited through a stimulus probe or contact(s) of the strip, yielded larger responses from the corresponding sensory mapped limb; that is, PTN SM resulted in larger lower limb muscle responses than those suggested by MN SM. LESSONS SM of the MN and PTN is effective for localizing eloquent cortical areas wherein the PTN is favored in surgery for mesial cortical tumors. The recorded amplitude of the cortical somatosensory evoked potential is a valuable criterion for defining the optimal location for DCS, despite an absent PR. The pathway at risk dictates the specifics of SM, which subsequently defines the optimal location for DCS.
PRIMATE: Processing in Memory Acceleration for Dynamic Token-pruning Transformers

Attention-based models such as Transformers represent the state of the art for various machine learning (ML) tasks. Their superior performance is often overshadowed by the substantial memory requirements and low data reuse opportunities. Processing in Memory (PIM) is a promising solution to accelerate Transformer models due to its massive parallelism, low data movement costs, and high memory bandwidth utilization. Existing PIM accelerators lack the support for algorithmic optimizations like dynamic token pruning that can significantly improve the efficiency of Transformers. We identify two challenges to enabling dynamic token pruning on PIM-based architectures: the lack of an in-memory top-k token selection mechanism and the memory underutilization problem from pruning. To address these challenges, we propose PRIMATE, a software-hardware co-design PIM framework based on High Bandwidth Memory (HBM). We initiate minor hardware modifications to conventional HBM to enable Transformer model computation and top-k selection. For software, we introduce a pipelined mapping scheme and an optimization framework for maximum throughput and efficiency. PRIMATE achieves $30.6\times$ improvement in throughput, $29.5\times$ improvement in space efficiency, and $4.3\times$ better energy efficiency compared to the current state-of-the-art PIM accelerator for Transformers.
Nonlinear Frequency Compression

Frequency lowering technologies offer an alternative amplification solution for severe to profound high frequency hearing losses. While frequency lowering technologies may improve audibility of high frequency sounds, the very nature of this processing can affect the perceived sound quality. This article reports the results from two studies that investigated the impact of a nonlinear frequency compression (NFC) algorithm on perceived sound quality. In the first study, the cutoff frequency and compression ratio parameters of the NFC algorithm were varied, and their effect on the speech quality was measured subjectively with 12 normal hearing adults, 12 normal hearing children, 13 hearing impaired adults, and 9 hearing impaired children. In the second study, 12 normal hearing and 8 hearing impaired adult listeners rated the quality of speech in quiet, speech in noise, and music after processing with a different set of NFC parameters. Results showed that the cutoff frequency parameter had more impact on sound quality ratings than the compression ratio, and that the hearing impaired adults were more tolerant to increased frequency compression than normal hearing adults. No statistically significant differences were found in the sound quality ratings of speech-in-noise and music stimuli processed through various NFC settings by hearing impaired listeners. These findings suggest that there may be an acceptable range of NFC settings for hearing impaired individuals where sound quality is not adversely affected. These results may assist an Audiologist in clinical NFC hearing aid fittings for achieving a balance between high frequency audibility and sound quality.
On Pattern-Avoiding Partitions

A set partition of size $n$ is a collection of disjoint blocks $B_1,B_2,\ldots$, $B_d$ whose union is the set $[n]=\{1,2,\ldots,n\}$. We choose the ordering of the blocks so that they satisfy $\min B_1 canonical sequence $\pi_1,\pi_2,\ldots,\pi_n$, with $\pi_i=j$ if $i\in B_j$. We say that a partition $\pi$ contains a partition $\sigma$ if the canonical sequence of $\pi$ contains a subsequence that is order-isomorphic to the canonical sequence of $\sigma$. Two partitions $\sigma$ and $\sigma'$ are equivalent , if there is a size-preserving bijection between $\sigma$-avoiding and $\sigma'$-avoiding partitions. We determine all the equivalence classes of partitions of size at most $7$. This extends previous work of Sagan, who described the equivalence classes of partitions of size at most $3$. Our classification is largely based on several new infinite families of pairs of equivalent patterns. For instance, we prove that there is a bijection between $k$-noncrossing and $k$-nonnesting partitions, with a notion of crossing and nesting based on the canonical sequence. Our results also yield new combinatorial interpretations of the Catalan numbers and the Stirling numbers.
Swimming Stroke Mechanical Efficiency and Physiological Responses of 100-m Backstroke with and without the use of paddles

Abstract The use of swimming aids during training contributes to greater swimming efficiency by the improvement of the swimming specific power of the athlete. The purpose of this study was to compare the swimming stroke technical characteristics and the physiological responses of swimming 100-m backstroke, with and without the use of paddles at maximum and sub-maximum intensities at the same swimming speed. Eight swimmers competing at the national level participated in this study. The measurements took place at 4 different sessions. At every session, each participant swam individually one 100-m backstroke swimming trial with or without paddles at the same speed and two levels of intensity (100% and 85% of maximum speed). The results revealed lower stroke length, greater stroke number and gliding length without the use of swimming paddles at both intensities. Βlood lactate concentration (10.03±2.96 vs. 5.85±2.23 mmol/l) and Rating of Perceived Exertion (17.43±2.07 vs. 12±2.82) were greater without the use of swimming paddles only at 100% of maximum speed. Thus, swimming backstroke with paddles compared to unaided swimming, at a similar speed, showed a greater efficiency at maximal but not at sub-maximal intensity.