Miracle-dz/UniFAR-FTUs huggingface dataset:
Drug Diffusion Along an Intact Mammalian Cochlea

Intratympanic drug administration depends on the ability of drugs to pass through the round window membrane (RW) at the base of the cochlea and diffuse from this location to the apex. While the RW permeability for many different drugs can be promoted, passive diffusion along the narrowing spiral of the cochlea is limited. Earlier measurements of the distribution of marker ions, corticosteroids, and antibiotics demonstrated that the concentration of substances applied to the RW was two to three orders of magnitude higher in the base compared to the apex. The measurements, however, involved perforating the cochlear bony wall and, in some cases, sampling perilymph. These manipulations can change the flow rate of perilymph and lead to intake of perilymph through the cochlear aqueduct, thereby disguising concentration gradients of the delivered substances. In this study, the suppressive effect of salicylate on cochlear amplification via block of the outer hair cell (OHC) somatic motility was utilized to assess salicylate diffusion along an intact guinea pig cochlea in vivo. Salicylate solution was applied to the RW and threshold elevation of auditory nerve responses was measured at different times and frequencies after application. Resultant concentrations of salicylate along the cochlea were calculated by fitting the experimental data using a mathematical model of the diffusion and clearing of salicylate in a tube of variable diameter combined with a model describing salicylate action on cochlear amplification. Concentrations reach a steady-state at different times for different cochlear locations and it takes longer to reach the steady-state at more apical locations. Even at the steady-state, the predicted concentration at the apex is negligible. Model predictions for the geometry of the longer human cochlea show even higher differences in the steady-state concentrations of the drugs between cochlear base and apex. Our findings confirm conclusions that achieving therapeutic drug concentrations throughout the entire cochlear duct is hardly possible when the drugs are applied to the RW and are distributed via passive diffusion. Assisted methods of drug delivery are needed to reach a more uniform distribution of drugs along the cochlea.
A Novel Acquisition Algorithm Based on PMF-apFFT for BOC Modulated Signals

Large Doppler shifts are inherent to high-speed relative motion between receiver and satellite and are likely to cause major problems during the code phase acquisition due to the introduced frequency ambiguity. In order to solve the problem of acquisition for the binary offset carrier (BOC) modulated the signal with large Doppler shift, a novel acquisition algorithm based on partial matched filter-all phase fast Fourier transform (PMF-apFFT) is proposed in this paper. In this method, all phase processing was adopted to weaken the effect of spectrum leakage after partial correlation, and two dimensional parallel searching for Doppler frequency on different code phases was completed by the maximum value after the cumulative average exceeding the threshold. The theoretical analysis and simulation results show that the correct code phase search and high precision estimation of Doppler frequency can be completed by the proposed algorithm at the same time. Compared with the traditional PMF-FFT acquisition algorithm, the proposed algorithm has stronger anti-noise performance and a better detection probability, and it is suitable for the complex communication environment of strong noise and large Doppler shift.
Emotion-Specific Facial Activation Maps Based on Infrared Thermal Image Sequences

Research on emotion recognition has recently started to gain increased attention. Inner emotions or thought activity can be determined by analyzing facial expression, behavioral responses, audio, and physiological signals. Facial expression is now recognized as an important form of non-verbal interaction. In this paper, emotion-specific activation maps were constructed to establish infrared thermal facial image sequences as an alternative approach to the determination of the correlation between emotional triggers and changes in facial temperature. During the testing process, data stored in the International Affective Picture System were used to create emotional clips that triggered three different types of emotion in the subjects, and their infrared thermal facial image sequences were simultaneously recorded. For processing, an image calibration protocol was first employed to reduce the variance produced by irregular micro-shifts in the faces of the subjects, followed by independent component analysis and statistical analysis protocols to create the facial emotional activation maps. The test results showed that the problem of selecting local regions when analyzing frame temperature had been resolved. The emotion-specific facial activation maps provide visualized results that facilitate the observation and understanding of information.
A Novel Modeling for Assessing Frequency Behavior During a Hydro-to-Thermal Plant Black Start Restoration Test

Northern electric grid of Italy was involved in a black start mock drill. This test took place on November 2016 in order to check the coordination and efficiency of all the operational staffs and the automatic regulators involved in the case of a real blackout scenario. This paper presents the results of a research carried out in collaboration with Terna Rete Italia (the Italian Transmission System Operator), in order to find strengths and weaknesses and eventually to upgrade the existing restoration plan. Starting from the measures coming from generating plants and substations bars, the model of frequency regulation system for both the participating hydro and thermal power plants is developed. This work gives the system operator an essential tool to understand many complex dynamics and phenomena occurred during the test. At the same time, a robust model simulating the system behavior with different grid configurations is presented: it gives the opportunity to enhance both the classical power system control theory and the black start practices.
Fixed Boundary Flows

We consider the fixed boundary flow with canonical interpretability as principal components extended on the non-linear Riemannian manifolds. We aim to find a flow with fixed starting and ending point for multivariate datasets lying on an embedded non-linear Riemannian manifold, differing from the principal flow that starts from the center of the data cloud. Both points are given in advance, using the intrinsic metric on the manifolds. From the perspective of geometry, the fixed boundary flow is defined as an optimal curve that moves in the data cloud. At any point on the flow, it maximizes the inner product of the vector field, which is calculated locally, and the tangent vector of the flow. We call the new flow the fixed boundary flow. The rigorous definition is given by means of an Euler-Lagrange problem, and its solution is reduced to that of a Differential Algebraic Equation (DAE). A high level algorithm is created to numerically compute the fixed boundary. We show that the fixed boundary flow yields a concatenate of three segments, one of which coincides with the usual principal flow when the manifold is reduced to the Euclidean space. We illustrate how the fixed boundary flow can be used and interpreted, and its application in real data.
Memory Performance of People with Different Dementia Severity for Different Semantic Hierarchies

ABSTRACT Background: Memory disorder is a significant symptom during early-stage Alzheimer’s disease (AD). Changes in semantic memory are frequently seen in terms of forgetting names, loss of word meanings, and difficulties in linguistic expression. Significant semantic degeneration is not a normal phenomenon in elderly persons, and it may be an important sign in the early stages of progression of AD. Methods: Thirty-four participants aged between 60 and 86 years were recruited for an experiment with a 3 × 4 × 2 factorial design that was conducted to explore the differences in semantic memory performance among controls with normal cognitive performance (NC), individuals classified as mildly cognitively impaired (MCI), and individuals with AD. Results: The performance of participants diagnosed with mild AD was poorest for the attribute category, and there was no difference in response to different word frequencies. Although those diagnosed with MCI performed similarly to healthy elderly participants in terms of semantic memory, their performance profiles for different semantic hierarchies were similar to those of participants with AD. Conclusion: Semantic memory had degraded among participants with AD and MCI, and the rate of semantic degeneration was different in different semantic hierarchies.
Diaphragm sniff ultrasound: Normal values, relationship with sniff nasal pressure and accuracy for predicting respiratory involvement in patients with neuromuscular disorders

Background In patients with neuromuscular disorders, assessment of respiratory function relies on forced vital capacity (FVC) measurements. Providing complementary respiratory outcomes may be useful for clinical trials. Diaphragm sniff ultrasound (US) is a noninvasive technique that can assess diaphragm function that may be affected in patients with neuromuscular disorders. Purpose We aimed to provide normal values of sniff diaphragm ultrasound, to assess the relationship between sniff diaphragm US, vital capacity (VC) and sniff nasal pressure. Additionally, we aimed to evaluate the diagnostic accuracy of sniff diaphragm US for predicting restrictive pulmonary insufficiency. Materials and methods We included patients with neuromuscular disorders that had been tested with a sniff diaphragm US and functional respiratory tests. Healthy subjects were also included to obtain normal diaphragm sniff ultrasound. We performed diaphragm tissue Doppler imaging (TDI) and time movement (TM) diaphragm echography combined with sniff maneuver. Results A total of 89 patients with neuromuscular diseases and 27 healthy subjects were included in our study. In patients, the median age was 32 years [25; 50] and the median FVC was 34% of predicted [18; 55]. Sniff diaphragm motion using TM ultrasound was significantly associated with sniff nasal pressure, both for the right hemidiaphragm (r = 0.6 p <0.0001) and the left hemidiaphragm (r = 0.63 p = 0.0008). Right sniff peak TDI velocity was also significantly associated with FVC (r = 0.72, p<0.0001) and with sniff nasal pressure (r = 0.66 p<0.0001). Sniff diaphragm ultrasound using either TM mode or TDI displayed significant accuracy for predicting FVC<60% with an area under curve (AUC) reaching 0.93 (p<0.0001) for the right sniff diaphragm ultrasound in TM mode and 0.86 (p<0.001) for right peak diaphragm TDI velocity. Conclusion Sniff diaphragm TM and TDI measures were significantly associated with sniff nasal pressure. Sniff diaphragm TM and TDI had a high level of accuracy to reveal respiratory involvement in patients with neuromuscular disorders. This technique is useful to assess and follow up diaphragm function in patients with neuromuscular disorders. It may be used as a respiratory outcome for clinical trials.
LitSense: making sense of biomedical literature at sentence level

Literature search is a routine practice for scientific studies as new discoveries build on knowledge from the past. Current tools (e.g. PubMed, PubMed Central), however, generally require significant effort in query formulation and optimization (especially in searching the full-length articles) and do not allow direct retrieval of specific statements, which is key for tasks such as comparing/validating new findings with previous knowledge and performing evidence attribution in biocuration. Thus, we introduce LitSense, which is the first web-based system that specializes in sentence retrieval for biomedical literature. LitSense provides unified access to PubMed and PMC content with over a half-billion sentences in total. Given a query, LitSense returns best-matching sentences using both a traditional term-weighting approach that up-weights sentences that contain more of the rare terms in the user query as well as a novel neural embedding approach that enables the retrieval of semantically relevant results without explicit keyword match. LitSense provides a user-friendly interface that assists its users to quickly browse the returned sentences in context and/or further filter search results by section or publication date. LitSense also employs PubTator to highlight biomedical entities (e.g. gene/proteins) in the sentences for better result visualization. LitSense is freely available at https://www.ncbi. nlm.nih. gov/research/litsense.
A distributed adaptive scheme for multiagent systems

In traditional adaptive control, the certainty equivalence principle suggests a two‐step design scheme. A controller is first designed for the ideal situation assuming the uncertain parameter was known, and it renders a Lyapunov function. Then, the uncertain parameter in the controller is replaced by its estimation that is updated by an adaptive law along the gradient of Lyapunov function. This principle does not generally work for a multiagent system as an adaptive law based on the gradient of (centrally constructed) Lyapunov function cannot be implemented in a distributed fashion, except for limited situations. In this paper, we propose a novel distributed adaptive scheme, not relying on gradient of Lyapunov function, for general multiagent systems. In this scheme, asymptotic consensus of a second‐order uncertain multiagent system is achieved in a network of directed graph.
Competition for Andersen ’ s Clients

We examine the competition among Big 4 firms for Andersen’s public clients during and after its demise in 2002. Andersen’s failure provides a quasi laboratory to investigate how audit firms compete for new clients. Our analysis focuses primarily on the acquisition by Big 4 firms of some, but not all, of Andersen’s individual offices in the United States, and the resulting impact on public clients. The United States Congress expressed concern about the failure of Andersen when it required the GAO to study the competitive nature of audit markets as part of the Sarbanes Oxley Act (GAO 2003). We build on the original GAO study by incorporating office purchases into the analysis of competition for Andersen’s public clients. We use news reports to construct a database that differentiates between Andersen offices that were effectively purchased or not purchased by the surviving Big 4 firms.1 This database enables us to explore the factors associated with Big 4 office purchases, differences in strategies used to acquire Andersen’s clients, and the impact of these different acquisition strategies on audit fees. We identify 65 Andersen offices that served public clients in 2001. Big 4 firms purchased 39 offices and three local industry practice units from large offices. Based on these data, we consider four types of Andersen client switches: (a) EARLY_SWITCHERS: clients who switched prior to the purchase of their Andersen office, or if the office was not purchased, prior to the first Andersen
Investigating the influence of structure of user performance with UML interaction diagrams

The importance of structure in specifications and programs has long been recognised in both theoretical research and empirical studies, particularly with reference to the ease with which a reader can understand information representations. In this paper we report on an investigation, using diagrams from the Unified Modelling Language (UML), into whether different structures applied to the same information affect the ease with which readers can understand the information. Our hypothesis was that one of the structure types would produce diagrams that were easier for readers to understand than the other. However, although three studies were carried out, results in each case showed that participants performed equally well on diagrams with each type of structure. We conclude that the difference between two types of structure appears less important than the fact that the two diagram types provide both visible structure and abstractions that the reader may reason with.
Left Shifting of Language Related Activity Induced by Bihemispheric tDCS in Postacute Aphasia Following Stroke

Both anodal transcranial direct current stimulation (tDCS) of the left IFG and cathodal stimulation of the right IFG were shown to improve rehabilitation of stroke patients with Broca’s aphasia. The study aimed at assessing the impact of a bihemispheric IFG stimulation compared to sham on postacute non-fluent aphasia. Twelve patients with non-fluent aphasia were included at least 4 weeks following cerebral stroke. Ten daily sessions of 2 mA bihemispheric verum or sham tDCS (anode on left IFG and cathode on right IFG) were performed concomitantly with individual language therapy in a double-blinded randomized controlled study with parallel group design. Language functions [i.e., communication (ANELT), picture naming and the Aachen aphasia test (AAT)] were assessed up to 1 month following tDCS. The picture naming task significantly improved (increased number of nouns) at the end of the tDCS procedure in the verum but not sham group. Improvements in the picture naming task and the communication task of the AAT at 4 weeks after tDCS procedure were only seen in the verum group. In patients with postacute cerebral stroke, repeated sessions of tDCS applied on both IFG concomitantly with language therapy were able to induce immediate effects on picture naming presumably due to an early left shift of language-associated function that maintained for 4 weeks. Effects on clinically relevant communicative abilities are likely.
Glutamatergic neurons of the gigantocellular reticular nucleus shape locomotor pattern and rhythm in the freely behaving mouse

Because of their intermediate position between supraspinal locomotor centers and spinal circuits, gigantocellular reticular nucleus (GRN) neurons play a key role in motor command. However, the functional contribution of glutamatergic GRN neurons in initiating, maintaining, and stopping locomotion is still unclear. Combining electromyographic recordings with optogenetic manipulations in freely behaving mice, we investigate the functional contribution of glutamatergic brainstem neurons of the GRN to motor and locomotor activity. Short-pulse photostimulation of one side of the glutamatergic GRN did not elicit locomotion but evoked distinct motor responses in flexor and extensor muscles at rest and during locomotion. Glutamatergic GRN outputs to the spinal cord appear to be gated according to the spinal locomotor network state. Increasing the duration of photostimulation increased motor and postural tone at rest and reset locomotor rhythm during ongoing locomotion. In contrast, photoinhibition impaired locomotor pattern and rhythm. We conclude that unilateral activation of glutamatergic GRN neurons triggered motor activity and modified ongoing locomotor pattern and rhythm.
Multisensory Data-Driven Health Degradation Monitoring of Machining Tools by Generalized Multiclass Support Vector Machine

Health degradation monitoring of machining tools is of great importance in industrial application field. In this paper, a novel multisensory data-driven health degradation monitoring system schema for the machining tools is proposed by using a generalized multiclass support vector machine (GenSVM). In this schema, multidimensional feature extraction is implemented in the time domain, frequency domain, and time–frequency domain based on the time domain statistical analysis, power spectrum analysis, and complete ensemble empirical mode decomposition with adaptive noise, respectively. On the basis, effective features that are strongly associated with the degradation process are picked out using a Pearson correlation coefficient. Meanwhile, a new and flexible GenSVM model is constructed to identify the health state of machining tools, which integrates a simplex encoding and iterative majorization optimization algorithm. A practical application case study is implemented to verify the effectiveness of the proposed method. The results show the superior performance of the proposed method compared with other standard methods.
The Nature of Ionized Gas in the Milky Way Galactic Fountain

We address the spatial scale, ionization structure, mass, and metal content of gas at the Milky Way disk–halo interface detected as absorption in the foreground of seven closely spaced, high-latitude halo blue horizontal branch stars with heights z = 3–14 kpc. We detect transitions that trace multiple ionization states (e.g., Ca ii, Fe ii, Si iv, C iv) with column densities that remain constant with height from the disk, indicating that the gas most likely lies within z < 3.4 kpc. The intermediate ionization state gas traced by C iv and Si iv is strongly correlated over the full range of transverse separations probed by our sight lines, indicating large, coherent structures greater than 1 kpc in size. The low ionization state material traced by Ca ii and Fe ii does not exhibit a correlation with either NH i or transverse separation, implying cloudlets or clumpiness on scales less than 10 pc. We find that the observed ratio log(NSi iv/NC iv), with a median value of −0.69 ± 0.04, is sensitive to the total carbon content of the ionized gas under the assumption of either photoionization or collisional ionization. The only self-consistent solution for photoionized gas requires that Si be depleted onto dust by 0.35 dex relative to the solar Si/C ratio, similar to the level of Si depletion in DLAs and in the Milky Way interstellar medium. The allowed range of values for the areal mass infall rate of warm, ionized gas at the disk−halo interface is 0.0003 < dMgas/dtdA [M⊙ kpc−2 yr−1] <0.006. Our data support a physical scenario in which the Milky Way is fed by complex, multiphase processes at its disk−halo interface that involve kiloparsec-scale ionized envelopes or streams containing parsec-scale, cool clumps.
Solver for the electronic V-representation problem of time-dependent density functional theory.

One route to numerically propagating quantum systems is time-dependent density functional theory (TDDFT). The application of TDDFT to a particular system's time evolution is predicated on V-representability which we have analyzed in a previous publication. Here we describe a newly developed solver for the scalar time-dependent Kohn-Sham potential. We present and interpret the force-balance equation central to our numerical method, describe details of its implementation, and present illustrative numerical results for one- and two-electron systems in both 1D and 3D grids. Innovations of our numerical implementation include the use of preconditioning when inverting the force-balance matrix and an improved propagation method obtaining the Kohn-Sham potential self-consistently at each step of the propagation. A new characterization of $V$-representability for one-electron systems is also included along with possible improvements and future directions.
Motion detail preserving optical flow estimation

We discuss the cause of a severe optical flow estimation problem that fine motion structures cannot always be correctly reconstructed in the commonly employed multi-scale variational framework. Our major finding is that significant and abrupt displacement transition wrecks small-scale motion structures in the coarse-to-fine refinement. A novel optical flow estimation method is proposed in this paper to address this issue, which reduces the reliance of the flow estimates on their initial values propagated from the coarser level and enables recovering many motion details in each scale. The contribution of this paper also includes adaption of the objective function and development of a new optimization procedure. The effectiveness of our method is borne out by experiments for both large- and small-displacement optical flow estimation.