Miracle-dz/UniFAR-FTUs huggingface dataset:
Challenging limits: Ultrastructure and size‐related functional constraints of the compound eye of Stigmella microtheriella (Lepidoptera: Nepticulidae)

With a body length of only 2 mm, the nepticulid Stigmella microtheriella (Stainton, 1854) is one of the smallest moths known to date. We investigated the optical design of its lemon‐shaped compound eyes, which measure 83.60 μm in anterior–posterior and 119.77 μm in dorso‐ventral direction. The eyes consist of about 123 facets, each of the latter just 9.9 μm in diameter. Transmission electron microscopy reveals an optical design with features intermediate between apposition and superposition optics similar to that known from two other small species of moths (one Nepticulid and one Gracillarid). Size‐related evolutionary adaptations of the ommatidial organization include (1) the involvement of only five rhabdomeres in the formation of the distal rhabdom (2) the complete absence of a rhabdomere of the eighth (= basal) retinula cell, (3) the “hourglass” shape of the rhabdom with a characteristic narrow waist separating distal from proximal portion, and (4) the reduction to one single layer of tracheoles as an adaptation to the overall restricted space available in this minute eye. J. Morphol. 2012. © 2012 Wiley Periodicals, Inc.
Adaptive Frequency sweep analysis for electromagnetic problems using the Thiele interpolating continued fractions

A direct rational approximation method based on Thiele interpolating continued fractions theory is proposed for fast frequency sweep analysis of electromagnetic problems. And an adaptive algorithm is also formed. Compared with the conventional rational approximation method, the proposed method can get a rational approximation directly without a great number of matrix inverse computations and doesn't need to allocate much memory for high derivatives of the dense impedance matrix. Meanwhile, the computation of surface currents by continued fractions can be sped up as compared with the traditional rational approximation. Numerical simulations for broad band scattering analysis of different shaped objects are discussed to shown the effectiveness of the present method.
Simulation of Gaussian random field in a ball

Abstract We address the problem of statistical simulation of a scalar real Gaussian random field inside the unit 3D ball. Two different methods are studied: (i) the method based on the known homogeneous isotropic power spectrum developed by Meschede and Romanowicz [M. Meschede and B. Romanowicz, Non-stationary spherical random media and their effect on long-period mantle waves, Geophys. J. Int. 203 2015, 1605–1625] and (ii) the method based on known radial and angular covariance functions suggested in this work. The first approach allows the extension of the simulation technique to the inhomogeneous or anisotropic case. However, the disadvantage of this approach is the lack of accurate statistical characterization of the results. The accuracy of considered methods is illustrated by numerical tests, including a comparison of the estimated and analytical covariance functions. These methods can be used in many applications in geophysics, geodynamics, or planetary science where the objective is to construct spatial realizations of 3D random fields based on a statistical analysis of observations collected on the sphere or within a spherical region.
Report on A Formally-Founded Model-Based Approach to Engineer Self-Adaptive Systems

Self-adaptive systems manage themselves to deal with uncertainties that can only be resolved during operation. A common approach to realize self-adaptation is by adding a feedback loop to the system that monitors the system and adapts it to realize a set of adaptation goals. ActivFORMS (Active FORmal Models for Self-adaptation) provides an end-to-end approach for engineering self-adaptive systems. ActivFORMS relies on feedback loops that consists of formally verified models that are directly deployed and executed at runtime to realize self-adaptation. At runtime, the approach relies on statistical verification techniques that allow efficient analysis of the possible options for adaptation. Further, ActivFORMS supports on-the-fly changes of adaptation goals and updates of the verified models to to meet the new goals. ActivFORMSi provides a tool-supported instance of ActivFORMS. The approach has been validates using an IoT application for building security monitoring. This report provides complementary material to the paper ``ActivFORMS: A Formally-Founded Model-Based Approach to Engineer Self-Adaptive Systems'' [Weyns and Iftikhar 2019].
Wasted Hospital Days Impair the Value of Length-of-Stay Variables in the Quality Assessment of Trauma Care

Hospital length of stay (LOS) is frequently used to evaluate the quality of trauma care but LOS may be impacted by nonmedical factors as well. We reviewed our experience with delays in patient discharge to determine its financial consequences and its impact on LOS. We performed an analysis of linked trauma registry and “delayed discharge” databases. Actual LOS (A-LOS) values were compared with calculated ideal LOS (I-LOS) values, and the per cent increase in LOS was calculated. Linear regression analysis was used to identify significant predictors of prolonged LOS. One thousand, five hundred and seventeen patients were studied, with an A-LOS of 6.54 days. Seven per cent of patients experienced discharge delays, resulting in 580 excess hospital days. Calculated I-LOS was 6.15 days, 6.34 per cent lower than A-LOS. Other I-LOS estimates were as much as 25 per cent lower than A-LOS. Estimated excess patient charges associated with delayed discharges were $4,000,000 to $15,000,000. Discharge delays are an infrequent, although costly, occurrence that has a significant impact on LOS. LOS therefore may not be an appropriate metric for assessing the quality of trauma care, and should only be used if it has been corrected for discharge delays. Concerted efforts should be directed towards identifying and correcting the factors responsible for delayed discharge in trauma patients.
Misunderstanding the preorganization concept can lead to confusions about the origin of enzyme catalysis

Understanding the origin of the catalytic power of enzymes has both conceptual and practical importance. One of the most important finding from computational studies of enzyme catalysis is that a major part of the catalytic power is due to the preorganization of the enzyme active site. Unfortunately, misunderstanding of the nontrivial preorganization idea lead some to assume that it does not consider the effect of the protein residues. This major confusion reflects a misunderstanding of the statement that the interaction energy of the enzyme group and the transition state (TS) is similar to the corresponding interaction between the water molecules (in the reference system) and the TS, and that the catalysis is due to the reorganization free energy of the water molecules. Obviously, this finding does not mean that we do not consider the enzyme groups. Another problem is the idea that catalysis is due to substrate preorganization. This more traditional idea is based in some cases on inconsistent interpretation of the action of model compounds, which unfortunately, do not reflect the actual situation in the enzyme active site. The present article addresses the above problems, clarifying first the enzyme polar preorganization idea and the current misunderstandings. Next we take a specific model compound that was used to promote the substrate preorganization proposal and establish its irrelevance to enzyme catalysis. Overall, we show that the origin of the catalytic power of enzymes cannot be assessed uniquely without computer simulations, since at present this is the only way of relating structure and energetics.
Markov Subsampling Based on Huber Criterion

Subsampling is an important technique to tackle the computational challenges brought by big data. Many subsampling procedures fall within the framework of importance sampling, which assigns high sampling probabilities to the samples appearing to have big impacts. When the noise level is high, those sampling procedures tend to pick many outliers and thus often do not perform satisfactorily in practice. To tackle this issue, we design a new Markov subsampling strategy based on Huber criterion (HMS) to construct an informative subset from the noisy full data; the constructed subset then serves as refined working data for efficient processing. HMS is built upon a Metropolis–Hasting procedure, where the inclusion probability of each sampling unit is determined using the Huber criterion to prevent over scoring the outliers. Under mild conditions, we show that the estimator based on the subsamples selected by HMS is statistically consistent with a sub-Gaussian deviation bound. The promising performance of HMS is demonstrated by extensive studies on large-scale simulations and real data examples.
Temporal Orthogonal Projection Inversion for EMI Sensing of UXO

We present a new approach for inverting time-domain electromagnetic data to recover the location and magnetic dipole polarizations of a limited number of buried objects. We form the multichannel electromagnetic induction (EMI) sensor data as a spatial-temporal response matrix (STRM). The rows of the STRM correspond to measurements sampled at different time channels from one sensor and the columns correspond to measurements sampled at the same time channel from different sensors. The singular value decomposition of the STRM produces the left and right singular vectors that are related to the sensor and the temporal spaces, respectively. If the effective rank of the STRM is r, then the first r singular vectors span signal subspaces (SS), and the remaining singular vectors span the noise subspaces. The original data are projected onto the SS, and the temporal orthogonal projection inversion (TOPI) uses these data in a nonlinear inverse problem to solve for source locations of the objects. The polarizations of the targets are then obtained by solving a linear optimization problem in the original data domain. We present theoretical and numerical analyses to investigate the singular value system of the STRM and the sensitivity of the TOPI to the size of an SS. Only a few subspace vectors are required to generate locations of the objects. The results are insensitive to the exact choice of rank, and this differs from usual methods that involve selecting the number of time channels to be used in the inversion and carefully estimating associated uncertainties. The proposed approach is evaluated using the synthetic and real multistatic EMI data.
The iron-sulfur clusters of dehydratases are primary intracellular targets of copper toxicity

Excess copper is poisonous to all forms of life, and copper overloading is responsible for several human pathologic processes. The primary mechanisms of toxicity are unknown. In this study, mutants of Escherichia coli that lack copper homeostatic systems (copA cueO cus) were used to identify intracellular targets and to test the hypothesis that toxicity involves the action of reactive oxygen species. Low micromolar levels of copper were sufficient to inhibit the growth of both WT and mutant strains. The addition of branched-chain amino acids restored growth, indicating that copper blocks their biosynthesis. Indeed, copper treatment rapidly inactivated isopropylmalate dehydratase, an iron-sulfur cluster enzyme in this pathway. Other enzymes in this iron-sulfur dehydratase family were similarly affected. Inactivation did not require oxygen, in vivo or with purified enzyme. Damage occurred concomitant with the displacement of iron atoms from the solvent-exposed cluster, suggesting that Cu(I) damages these proteins by liganding to the coordinating sulfur atoms. Copper efflux by dedicated export systems, chelation by glutathione, and cluster repair by assembly systems all enhance the resistance of cells to this metal.
Quantum Stream Learning

The exotic nature of quantum mechanics makes machine learning (ML) be different in the quantum realm compared to classical applications. ML can be used for knowledge discovery using information continuously extracted from a quantum system in a broad range of tasks. The model receives streaming quantum information for learning and decision-making, resulting in instant feedback on the quantum system. As a stream learning approach, we present a deep reinforcement learning on streaming data from a continuously measured qubit at the presence of detuning, dephasing, and relaxation. We also investigate how the agent adapts to another quantum noise pattern by transfer learning. Stream learning provides a better understanding of closed-loop quantum control, which may pave the way for advanced quantum technologies.
DEMONSTRATION OF THE CASIMIR FORCE IN THE 0.6 TO 6 MU M RANGE

The vacuum stress between closely spaced conducting surfaces, due to the modification of the zero-point fluctuations of the electromagnetic field,has been conclusively demonstrated. The measurement employed an electromechanical system based on a torsion pendulum. Agreement with theory at the level of 5{percent} is obtained. {copyright} {ital 1996} {ital The American Physical Society}
Assessing HIV Risk in Workplaces for Prioritizing HIV Preventive Interventions in Karnataka State, India

Objective: To develop a model for prioritizing economic sectors for HIV preventive intervention programs in the workplace. Methods: This study was undertaken in Karnataka state, India. A 3-stage survey process was undertaken. In the first stage, we reviewed secondary data available from various government departments, identified industries in the private sector with large workforces, and mapped their geographical distribution. In the second stage, an initial rapid risk assessment of industrial sectors was undertaken, using key-informant interviews conducted in relation to a number of enterprises, and in consultation with stakeholders. In the third stage, we used both quantitative (polling booth survey) and qualitative methods (key informant interviews, in-depth interviews, focus group discussions) to study high-risk sectors in-depth, and assessed the need and feasibility of HIV workplace intervention programs. Results: The highest risk sectors were found to be mining, garment/textile, sugar, construction/infrastructure, and fishing industries. Workers in all sectors had at best partial knowledge about HIV/AIDS, coupled with common misconceptions about HIV transmission. There were intersector and intrasector variations in risk and vulnerability across different geographical locations and across different categories of workers. This has implications for the design and implementation of workplace intervention programs. Conclusions: There is tremendous scope for HIV preventive interventions in workplaces in India. Given the variation in HIV risk across economic sectors and limited available resources, there will be increased pressure to prioritize intervention efforts towards high-risk sectors. This study offers a model for rapidly assessing the risk level of economic sectors for HIV intervention programs.
Genotoxicity of occupational exposure to wood dust: Micronucleus frequency and nuclear changes in exfoliated buccal mucosa cells

Occupational exposure to wood dust is associated with the occurrence of nasal cancer. In this study, we investigated micronuclei and nuclear changes (NCs: binucleates, karyorrhexis, karyolysis, and the “broken egg” effect) in exfoliated buccal cells of 20 workers exposed to wood dust and 20 age‐ and sex‐matched controls. Micronucleus frequency and the frequency of each of the NCs were significantly higher for wood workers than controls (P < 0.01). Cigarette smoking was associated with increased frequencies of micronuclei and NCs in the buccal mucosa epithelium cells of both the control and exposed groups. Our findings indicate that buccal cells of wood workers display increased levels of genotoxicity and toxicity, and that these biomarker responses may be related to the increased cancer risk among wood workers. Environ. Mol. Mutagen. 47:, 2006. © 2006 Wiley‐Liss, Inc.
Neuropeptide Y Y1 receptor mRNA in rodent brain: Distribution and colocalization with melanocortin‐4 receptor

The central neuropeptide Y (NPY) Y1 receptor (Y1‐R) system has been implicated in feeding, endocrine, and autonomic regulation. In the present study, we systematically examined the brain distribution of Y1‐R mRNA in rodents by using radioisotopic in situ hybridization histochemistry (ISHH) with a novel sensitive cRNA probe. Within the rat hypothalamus, Y1‐R–specific hybridization was observed in the anteroventral periventricular, ventromedial preoptic, suprachiasmatic, paraventricular (PVH), dorsomedial, ventromedial, arcuate, and mamillary nuclei. In the rat, Y1‐R mRNA expression was also seen in the subfornical organ, anterior hypothalamic area, dorsal hypothalamic area, and in the lateral hypothalamic area. In addition, Y1‐R hybridization was evident in several extrahypothalamic forebrain and hindbrain sites involved in feeding and/or autonomic regulation in the rat. A similar distribution pattern of Y1‐R mRNA was observed in the mouse brain. Moreover, by using a transgenic mouse line expressing green fluorescent protein under the control of the melanocortin‐4 receptor (MC4‐R) promoter, we observed Y1‐R mRNA expression in MC4‐R–positive cells in several brain sites such as the PVH and central nucleus of the amygdala. Additionally, dual‐label ISHH demonstrated that hypophysiotropic PVH cells coexpress Y1‐R and pro–thyrotropin‐releasing hormone mRNAs in the rat. These observations are consistent with the proposed roles of the central NPY/Y1‐R system in energy homeostasis. J. Comp. Neurol. 482:217–243, 2005. © 2004 Wiley‐Liss, Inc.
Evaluation of a Fully Automated Research Prototype for the Immediate Identification of Microorganisms from Positive Blood Cultures under Clinical Conditions

ABSTRACT A clinical laboratory evaluation of an intrinsic fluorescence spectroscopy (IFS)-based identification system paired to a BacT/Alert Virtuo microbial detection system (bioMérieux, Inc., Durham, NC) was performed to assess the potential for fully automated identification of positive blood cultures. The prototype IFS system incorporates a novel method combining a simple microbial purification procedure with rapid in situ identification via spectroscopy. Results were available within 15 min of a bottle signaling positive and required no manual intervention. Among cultures positive for organisms contained within the database and producing acceptable spectra, 75 of 88 (85.2%) and 79 of 88 (89.8%) were correctly identified to the species and genus level, respectively. These results are similar to the performance of existing rapid methods. IMPORTANCE A fully automated research platform was developed to identify microbial growth from positive blood cultures in <15 min. Because of the automated format, results can be generated during all shifts, with or without staffing, which in turn could promote more timely administration of target antimicrobial therapy. A fully automated research platform was developed to identify microbial growth from positive blood cultures in <15 min. Because of the automated format, results can be generated during all shifts, with or without staffing, which in turn could promote more timely administration of target antimicrobial therapy.
The effect of head-related filtering and ear-specific decoding bias on auditory attention detection

Objective. We consider the problem of Auditory Attention Detection (AAD), where the goal is to detect which speaker a person is attending to, in a multi-speaker environment, based on neural activity. This work aims to analyze the influence of head-related filtering and ear-specific decoding on the performance of an AAD algorithm. Approach. We recorded high-density EEG of 16 normal-hearing subjects as they listened to two speech streams while tasked to attend to the speaker in either their left or right ear. The attended ear was switched between trials. The speech stimuli were administered either dichotically, or after filtering using Head-Related Transfer Functions (HRTFs). A spatio-temporal decoder was trained and used to reconstruct the attended stimulus envelope, and the correlations between the reconstructed and the original stimulus envelopes were used to perform AAD, and arrive at a percentage correct score over all trials. Main results. We found that the HRTF condition resulted in significantly higher AAD performance than the dichotic condition. However, speech intelligibility, measured under the same set of conditions, was lower for the HRTF filtered stimuli. We also found that decoders trained and tested for a specific attended ear performed better, compared to decoders trained and tested for both left and right attended ear simultaneously. In the context of the decoders supporting hearing prostheses, the former approach is less realistic, and studies in which each subject always had to attend to the same ear may find over-optimistic results. Significance. This work shows the importance of using realistic binaural listening conditions and training on a balanced set of experimental conditions to obtain results that are more representative for the true AAD performance in practical applications.
A ±0.4°C (3σ) −70 to 200°C time-domain temperature sensor based on heat diffusion in Si and SiO2

Despite the increasing use of ICs at very high temperatures (>;150°C) in automotive and industrial applications, sensing such temperatures is still mostly done with discrete thermocouples or thermistors. This is because conventional integrated temperature sensors are based on BJTs, which have a strongly process-, stress- and temperature-dependent saturation current (Is). Together with other leakage currents, this leads to rapidly increasing temperature errors at high temperatures: up to ±3.0°C at 200°C [1].
Enhancement of 26S Proteasome Functionality Connects Oxidative Stress and Vascular Endothelial Inflammatory Response in Diabetes Mellitus

Objective—Although the connection of oxidative stress and inflammation has been long recognized in diabetes mellitus, the underlying mechanisms are not fully elucidated. This study defined the role of 26S proteasomes in promoting vascular inflammatory response in early diabetes mellitus. Methods and Results—The 26S proteasome functionality, markers of autophagy, and unfolded protein response were assessed in (1) cultured 26S proteasome reporter cells and endothelial cells challenged with high glucose, (2) transgenic reporter (UbG76V–green fluorescence protein) and wild-type (C57BL/6J) mice rendered diabetic, and (3) genetically diabetic (Akita and OVE26) mice. In glucose-challenged cells, and also in aortic, renal, and retinal tissues from diabetic mice, enhanced 26S proteasome functionality was observed, evidenced by augmentation of proteasome (chymotrypsin-like) activities and reduction in 26S proteasome reporter proteins, accompanied by increased nitrotyrosine-containing proteins. Also, whereas inhibitor of the nuclear factor &kgr;-light-chain-enhancer of activated B cells &agr; proteins were decreased, an increase was found in nuclear factor &kgr;-light-chain-enhancer of activated B cells (NF-&kgr;B) nucleus translocation, which enhanced the NF-&kgr;B–mediated proinflammatory response, without affecting markers of autophagy or unfolded protein response. Importantly, the alterations were abolished by MG132 administration, small interfering RNA knockdown of PA700 (proteasome activator protein complex), or superoxide scavenging in vivo. Conclusion—Early hyperglycemia enhances 26S proteasome functionality, not autophagy or unfolded protein response, through peroxynitrite/superoxide-mediated PA700-dependent proteasomal activation, which elevates NF- ĸB-mediated endothelial inflammatory response in early diabetes mellitus.