Miracle-dz/UniFAR-FTUs huggingface dataset:
FASN expression, angiogenesis and lymphangiogenesis in central and peripheral giant cell lesions

Central giant cell lesion (CGCL) and peripheral giant cell lesion (PGCL) are non-neoplastic proliferative processes of the jaws. PGCL is a reactive process induced by irritant local factors and CGCL is an intra-osseous lesion of unknown etiology. Both lesions exhibit similar histologic features showing abundant mononuclear cells, admixed with a large number of multinucleated giant cells and a rich vascularized stroma with extravasated erythrocytes, hemosiderin deposition, and blood-filled pools. Recent studies have linked fatty acid synthase (FASN) with angiogenesis. Objective To evaluate angiogenesis and lymphangiogenesis and their relationship with FASN expression in CGCL and PGCL. Material and Methods Thirteen CGCL and 14 PGCL of the jaws were selected for immunoexpression of FASN; CD34 and CD105 (to assess blood microvessel density [MVD] and microvessel area [MVA]); and D2-40 (to assess lymphatic MVD and MVA). Results Within PGCL and CGCL, MVD-CD34 was signifcantly higher than MVD-CD10S, followed by MVD-D2-40. Moreover, a signifcantly higher number of FASN-positive multinucleated giant cells than mononuclear cells were observed. Between PGCL and CGCL, only MVD-CD34 and all MVA were signifcantly higher in PGCL. Positive correlation between MVA-CD10S with FASNpositive mononuclear cells in both lesions was observed. Conclusions Our results show both lesions exhibiting similar levels of FASN expression and neoangiogenesis, suggesting constitutive processes that regulate tissue maintenance.
Low Complexity Modem Structure for OFDM-Based Orthogonal Time Frequency Space Modulation

Orthogonal time frequency space (OTFS) modulation is a 2-D signaling technique that has recently emerged in the literature to tackle the time-varying (TV) wireless channels. OTFS deploys the Doppler-delay plane to multiplex the transmit data where the time variations of the TV channel are integrated over time and hence the equivalent channel relating the input and output of the system boils down to a time-invariant one. This signaling technique can be implemented on the top of a given multicarrier waveform with the addition of precoding and post-processing units to the modulator and demodulator. In this letter, we present discrete-time formulation of an orthogonal frequency division multiplexing-based OTFS system. We argue against deployment of window functions at the OTFS transmitter in realistic scenarios and thus limit any sort of windowing to the receiver side. We study the channel impact in discrete-time providing deeper insights into OTFS systems. Moreover, our derivations lead to simplified modulator and demodulator structures that are far simpler than those in the literature.
Evaluating Model Performance Through a User-Centric Explainable Framework for Probabilistic Load Forecasting Models

Load forecasting models ensure efficient, secure, and stable operation of the modern power system. Probabilistic forecasting accounts for uncertainties associated with missing features that are often overlooked by deterministic approaches. However, machine learning-based probabilistic models are complicated. This paper proposes a user-centric explainable AI framework that presents global and local interpretations aligned with the expertise and explanation needs of the targeted user. The overall influence of temporal and spatial exogenous features at the model development stage is evaluated using the Permutation Feature Importance technique. Such an explanation provides a holistic picture of the knowledge gained by the Gradient Boosting Regressor-based probabilistic load forecasting model. Further-more, the proposed framework suggests the implementation of SHapely Additive exPlanations (SHAP) at the post-deployment stage for individual forecast instances. Local explanations provided by SHAP are used to distinguish between interval forecasts with higher and lower forecast accuracy. Such distinction is applied for both the lower and upper bounds of the forecast interval. This is specifically useful for the non-AI expert end-users that need load forecasts for their strategizing their daily operations. This work is validated on the Kaggle data set on the national load demand of Panama supported with several other exogenous features such as weather-related quantities, holidays, and date-time details. Results show the efficacy of the proposed framework and its ability to provide user-friendly interpretations aligned with users' explanation goals.
Performance Evaluation of Active Islanding-Detection Algorithms in Distributed-Generation Photovoltaic Systems: Two Inverters Case

Grid-connected photovoltaic (PV) inverters employ an islanding-detection functionality in order to determine the status of the electrical grid. In fact, the inverter must be stopped once the islanding operating mode is detected according to standards and grid-code limits. Diverse islanding-detection algorithms have been proposed in literature to cope with this safety requirement. Among them, active methods based on the deliberate perturbation of the inverter behavior can minimize the so-called nondetection zone, which is a range of conditions in which the inverter does not recognize that it is operating in an undesired island. In most cases, the performances of these methods have been analyzed considering a highly dispersed generation scheme, where only one distributed-generation power system is connected to the local electrical power system (EPS). However, in some studies, it has been highlighted that if two or more PV inverters are connected to the same local EPS, their anti-islanding algorithms do not behave ideally and can fail in detecting the islanding condition. However, there is no systematic study that has investigated the overall capability of different anti-islanding methods employed on several inverters connected to the same EPS to detect islanding condition. This paper is a first attempt to carry out a systematic study of the performances of the most common active detection methods in a case of two inverters connected to the same EPS. In order to evaluate the global capability of the two systems to detect islanding condition, a new performance index is introduced and applied also to the case when the two inverters employ different anti-islanding algorithms.
Using fNIRS in Usability Testing: Understanding the Effect of Web Form Layout on Mental Workload

Amongst the many tasks in our lives, we encounter web forms on a regular basis, whether they are mundane like registering for a website, or complex and important like tax returns. There are many aspects of Usability, but one concern for user interfaces is to reduce mental workload and error rates. Whilst most assessment of mental workload is subjective and retrospective reporting by users, we examine the potential of functional Near Infrared Spectroscopy (fNIRS) as a tool for objectively and concurrently measuring mental workload during usability testing. We use this technology to evaluate the design of three different form layouts for a car insurance claim process, and show that a form divided into subforms increases mental workload, contrary to our expectations. We conclude that fNIRS is highly suitable for objectively examining mental workload during usability testing, and will therefore be able to provide more detailed insight than summative retrospective assessments. Further, for the fNIRS community, we show that the technology can easily move beyond typical psychology tasks, and be used for more natural study tasks.
Ketamine-Induced Oscillations in the Motor Circuit of the Rat Basal Ganglia

Oscillatory activity can be widely recorded in the cortex and basal ganglia. This activity may play a role not only in the physiology of movement, perception and cognition, but also in the pathophysiology of psychiatric and neurological diseases like schizophrenia or Parkinson's disease. Ketamine administration has been shown to cause an increase in gamma activity in cortical and subcortical structures, and an increase in 150 Hz oscillations in the nucleus accumbens in healthy rats, together with hyperlocomotion. We recorded local field potentials from motor cortex, caudate-putamen (CPU), substantia nigra pars reticulata (SNr) and subthalamic nucleus (STN) in 20 awake rats before and after the administration of ketamine at three different subanesthetic doses (10, 25 and 50 mg/Kg), and saline as control condition. Motor behavior was semiautomatically quantified by custom-made software specifically developed for this setting. Ketamine induced coherent oscillations in low gamma (50 Hz), high gamma (80 Hz) and high frequency (HFO, 150 Hz) bands, with different behavior in the four structures studied. While oscillatory activity at these three peaks was widespread across all structures, interactions showed a different pattern for each frequency band. Imaginary coherence at 150 Hz was maximum between motor cortex and the different basal ganglia nuclei, while low gamma coherence connected motor cortex with CPU and high gamma coherence was more constrained to the basal ganglia nuclei. Power at three bands correlated with the motor activity of the animal, but only coherence values in the HFO and high gamma range correlated with movement. Interactions in the low gamma band did not show a direct relationship to movement. These results suggest that the motor effects of ketamine administration may be primarily mediated by the induction of coherent widespread high-frequency activity in the motor circuit of the basal ganglia, together with a frequency-specific pattern of connectivity among the structures analyzed.
Phylogeny of Hirsutella species (Ophiocordycipitaceae) from the USA: remedying the paucity of Hirsutella sequence data

Hirsutella (Ophiocordycipitaceae: Hypocreales) is a genus of insect, mite, and nematode pathogens with an asexual morph, which generally produce a mucilaginous cluster of one or several conidia on phialides that are basally subulate and taper to a fine neck. The generic name Hirsutella has been proposed for suppression in favour of Ophiocordyceps as a consequence of the ending of dual nomenclature for different morphs of pleomorphic fungi in 2011. Though the generic name is well established, geographically dispersed, and speciose, exceptionally few sequences are available in online databases. We examined 46 isolates of 23 Hirsutella species from the USA, curated by the USDA-ARS Collection of Entomopathogenic Fungal Cultures (ARSEF Culture Collection), that previously had not been molecularly characterized and produced a phylogeny of these organisms; we included previously published Hirsutella and Ophiocordyceps taxa. In producing the largest phylogeny of Hirsutella isolates so far, we provide: (1) context for discussing previously-hypothesized relationships; (2) evidence for revisions as taxonomic transitions move forward; and (3) available molecular data to be incorporated into further evolutionary studies of Ophiocordycipitaceae.
Research on collaborative concept design integrating the application of virtual reality and DFMA

Because the concept design phase in the product initializing stage is usually the key for defining the cost and the quality of the product, this draws an intention to the purpose of using design for manufacturing and assembly (DFMA) in this stage in order to achieve optimal design from the very beginning of a product development project. On the other hand, because available product development management (PDM) systems do not provide a good communication environment which helps developing better design concepts, this research uses not only DFMA for innovative concept design and filtering process, but also virtual reality (VR) technologies for visualized collaborative concept-design communication. Based on these ideas, this research performs a complete system analysis and design process for a collaborative concept design system. The outcome of this research is able to resolve communication and interaction problems during concept-design phase.
PASTEL: a parameterized memory characterization system

PASTEL is a parameterized memory characterization system which extracts the characteristics of ASIC on-chip-memories such as delay, timing and power consumption which are important in LSI logic design. PASTEL is a fully-automated process from exact wire-RC extraction through circuit reduction, input vector generation, waveform measurement, data-sheet and library creation. The circuit reduction scheme can reduce the circuit simulation time by 2 order of magnitude while maintaining delay error within 100 ps of exact simulation.
Production of lignosulfonate in NSSC‐based biorefinery

The spent liquor (SL) of a neutral sulfite semichemical (NSSC) pulping process contains a considerable amount of lignocelluloses and is treated in wastewater systems. The lignocelluloses, however, can be used for producing value‐added products if they are isolated from the SL. In this article, solvent treatment (mixing acetone, ethanol, or isopropyl with SL) was used as a method for isolating lignosulfonate from SL. The maximum lignosulfonate removal was obtained via mixing isopropyl alcohol with SL at the weight ratio of 20/80, room temperature, and 5.7 pH. The results also showed that the molecular weight and anionic charge density of the precipitates were in the range of 5,000–70,000 g/mol and 0.2–1.8 meq/g, respectively. Based on these results, a process was proposed for isolating lignosulfonate from SL and converting the NSSC process to an NSSC‐based biorefinery. © 2015 American Institute of Chemical Engineers Biotechnol. Prog. , 31:1508–1514, 2015
Cloud-Based Personalization of New Advertising and e-Commerce Models for Video Consumption

Over the last few years, we have witnessed a generalization of the consumption of video contents through different media (computers, television, mobile phones, tablets,…) that converge into a unified user experience in an (almost) all-IP technological environment. At the same time, there have been significant advances in the generation and characterization of multimedia contents, due to the advent of social networking and the consolidation of standards like moving picture experts group (MPEG)-4 and MPEG-7. Finally, it is becoming easier and more natural to interact with multimedia contents, thanks to devices like tactile screens and touchpads. Overall, this landscape enables great possibilities for advertising and e-commerce, far beyond the traditional business models of broadcast TV. In this paper, we present a novel realization of two non-invasive advertising and e-commerce models to exploit those possibilities, grounded on a cloud-based personalization engine. This system cannot only identify the most interesting products to advertise to each user at any time, but also compose personalized applications on the fly, ready to run on different consumer device platforms. Our experiments show that this proposal can be very positively perceived by the end users.
Optical depths and time-scale distributions in Galactic microlensing

We present microlensing calculations for a Galactic model based on that of Han & Gould, which is empirically normalized by star counts. We find good agreement between this model and data recently published by the MACHO and OGLE collaborations for the optical depth in various Galactic fields, and the trends thereof with Galactic longitude l and latitude b. We produce maps of optical depth and, by adopting simple kinematic models, of average event time-scales for microlensing towards the Galactic bulge. We also find that our model predictions are in reasonable agreement with the OGLE data for the expected time-scale distribution. We show that the fractions of events with very long and short time-scales owing to a lens of mass M are weighted by M 2 n(M) dM and M -1 n(M)dM, respectively, independent of the density and kinematics of the lenses.
An Ultra-Efficient Key Recovery Attack on the Lightweight Stream Cipher A2U2

In this letter we report on an ultra-efficient key recovery attack under the chosen-plaintext-attack model against the stream cipher A2U2, which is the most lightweight cryptographic primitive (i.e., it costs only 284 GE in hardware implementation) proposed so far for low-cost Radio Frequency Identification (RFID) tags. Our attack can fully recover the secret key of the A2U2 cipher by only querying the A2U2 encryption twice on the victim tag and solving 32 sparse systems of linear equations (where each system has 56 unknowns and around 28 unknowns can be directly obtained without computation) in the worst case, which takes around 0.16 second on a Thinkpad T410 laptop.
MODEL-BASED DEPLOYMENT WITH AUTOFOCUS : A FIRST CUT

Embedded control applications have to meet detailed performance requirements on their interactions with the external environment. Examples for such requirements include response times, execution rates, and low-level interactions with hardware. Current approaches to embedded real-time software development are often code-centric and do not allow predictions about the satisfiability of performance constraints. The underlying platform is an intrinsic part of the design, yielding poor portability. We describe model based deployment, an approach to extend the capabilities of the AutoFOCUS software development method towards the design and implementation of distributed real-time systems. We show how the technical architecture can be expressed in terms of our modeling language, and how performance predictions can be drawn from the system model. Our goal is to define an integrated approach to design, verification, and testing for distributed reactive systems with special consideration of the platform properties.
Predictors of Collegiate Student-Athletes' Susceptibility to Stereotype Threat

The present investigation sought to determine the extent to which collegiate student-athletes are susceptible to stereotype threat and the factors that predict it. We proposed a structural equation model (SEM) by which a perceived coach's positive regard for an athlete's academic ability, athletic identity, and academic identity predicts the degree of perceived stereotype threat while controlling for gender, race/ethnicity, type of sport, and division level. Also hypothesized, athletic and academic identities mediate the coach's attitude toward academics in predicting susceptibility to stereotype threat. Survey responses from 318 collegiate athletes showed the coach's regard for an athlete's academic ability emerged as a significant predictor of stereotype threat. A coach's regard for academic ability had a significant negative relationship with athletic identity, which, in turn, had a significant positive relationship with stereotype threat.
Lightweight Specifications for Parallel Correctness

With the spread of multicore processors, it is increasingly necessary for programmers to write parallel software. Yet writing correct parallel software with explicit multithreading remains a difficult undertaking. Though many tools exist to help test, debug, and verify parallel programs, such tools are often hindered by a lack of any specification from the programmer of the intended, correct parallel behavior of his or her software. In this dissertation, we propose three novel lightweight specifications for the parallelism correctness of multithreaded software: semantic determinism, semantic atomicity, and nondeterministic sequential specifications for parallelism correctness. Our determinism specifications enable a programmer to specify that any run of a parallel program on the same input should deterministically produce the same output, despite the nondeterministic interleaving of the program's parallel threads of execution. Key to our determinism specifications are our proposed bridge predicates . predicates that compare pairs of program states from different executions for semantic equivalence. Our atomicity specifications use bridge predicates to generalize traditional atomicity, enabling a programmer to specify that regions of a parallel or concurrent program are, at a high-level, free from harmful interference by other threads. Finally, our nondeterministic sequential (NDSeq) specifications enable a programmer to completely specify the parallelism correctness of a multithreaded program with a sequential but nondeterministic version of the program and, further, enable a programmer to test, debug, and verify functional correctness sequentially, on the nondeterministic sequential program. We show that our lightweight specifications for parallelism correctness enable us to much more effectively specify, test, debug, and verify the use of parallelism in multithreaded software, independent of complex and fundamentally-sequential functional correctness. We show that we can easily write determinism, atomicity, and nondeterministic sequential (NDSeq) specifications for a number of parallel Java benchmarks. We propose novel testing techniques for checking that a program conforms to its determinism, atomicity, or nondeterministic sequential specification, and we apply these techniques to find a number of parallelism errors in our benchmarks. Further, we propose techniques for automatically inferring a likely determinism or NDSeq specification for a parallel program, given a handful of representative executions.
Pseudomonas fluorescens and Glomus mosseae Trigger DMI3-Dependent Activation of Genes Related to a Signal Transduction Pathway in Roots of Medicago truncatula1

Plant genes induced during early root colonization of Medicago truncatula Gaertn. J5 by a growth-promoting strain of Pseudomonas fluorescens (C7R12) have been identified by suppressive subtractive hybridization. Ten M. truncatula genes, coding proteins associated with a putative signal transduction pathway, showed an early and transient activation during initial interactions between M. truncatula and P. fluorescens, up to 8 d after root inoculation. Gene expression was not significantly enhanced, except for one gene, in P. fluorescens-inoculated roots of a Myc−Nod− genotype (TRV25) of M. truncatula mutated for the DMI3 (syn. MtSYM13) gene. This gene codes a Ca2+ and calmodulin-dependent protein kinase, indicating a possible role of calcium in the cellular interactions between M. truncatula and P. fluorescens. When expression of the 10 plant genes was compared in early stages of root colonization by mycorrhizal and rhizobial microsymbionts, Glomus mosseae activated all 10 genes, whereas Sinorhizobium meliloti only activated one and inhibited four others. None of the genes responded to inoculation by either microsymbiont in roots of the TRV25 mutant. The similar response of the M. truncatula genes to P. fluorescens and G. mosseae points to common molecular pathways in the perception of the microbial signals by plant roots.
Modeling Aggregate MAC Flow Throughput and Fairness in Non-Saturated IEEE 802.11 Based Wireless Mesh Networks

In this paper, we study the trade-off between the aggregate MAC flow throughput and the fairness in IEEE 802.11 based wireless mesh networks (WMNs) that utilize scheduling on top of the CSMA/CA access scheme. We use a toy WMN topology to allow us to understand easily this trade-off and propose an analytical model to study the interaction between contending links in this topology. Based on this model, we formulate the bandwidth scheduling problem as an aggregate MAC flow throughput maximization problem subject to the fairness requirements dictated by the scheduler. This study is dictated by the need to understand the limits of such scheduling algorithms which have proliferated in recent years to balance the throughput and fairness of WMNs without modifying the CSMA/CA protocol or the binary exponential backoff due to the non programmability of the MAC and backoff procedure in modern commercial Wi-Fi chipset. As an example, we evaluate our previously proposed bandwidth scheduling mechanism - the so-called distributed fair MAC scheduler (DFMS) to validate our model on one hand and demonstrate the efficiency of our scheduler on the other.