Miracle-dz/UniFAR-FTUs huggingface dataset:
Measuring brain temperature without a thermometer

Temperature has profound effects on a wide range of parameters of neural activity at various scales (Hodgkin and Katz, 1949). At the cell level, ionic currents, membrane potential, input resistance, action potential amplitude, duration and propagation, and synaptic transmission have all been shown to be affected by temperature variations (Hodgkin and Katz, 1949; Kullmann and Asztely, 1998; Volgushev et al., 2000a,b; Fujii et al., 2002). At mesoscopic scales of neural activity, temperature changes can steer network activity toward different functional regimes (Reig et al., 2010), affecting the duration, frequency and firing rate of activated states during slow frequency oscillations, and the ability to end these states (Compte et al., 2003). Temperature also has a substantial effect on chemical reaction rates (Swan, 1974), and affects the blood oxygen saturation level by changing haemoglobin affinity for oxygen (Guyton, 1987). Furthermore, cooling reduces metabolic processes (Esmann and Skou, 1988), and has been used to silence cortical areas to study their function (Uyeda and Fuster, 1967). While from single cell to mesoscopic levels temperature can directly be measured, at the system level of non-invasive studies using electroencephalogram or functional magnetic resonance, it can only be estimated indirectly, using the temperature dependence of the magnetic resonance signal's frequency (Hindman, 1966; Parker et al., 1983; Kuroda et al., 1996). Furthermore, a theoretical model of brain temperature (Yablonskiy et al., 2000; Sukstankii and Yablonskiy, 2006) allows inferring from functional magnetic resonance data that functional stimulation can induce local brain temperature fluctuations of up to ±1°C with respect to resting temperature, by locally changing the balance between metabolic heat production and heat removal by blood flow. The potential impact of temperature modulations on functional brain activity is significant. Given a temperature effect on blood oxygen saturation levels of several percent/1°C (Guyton, 1987), and an estimated average brain van't Hoff temperature coefficient Q10 (the factor by which a reaction rate increases for 10°C increases) of 2,3 (Swan, 1974), the observed temperature fluctuations may lead to sizeable changes in blood oxygen saturation levels and to >2% variations in chemical reaction rates. Here we propose a way to directly quantify temperature from system-level brain recordings, and show how it can be used to characterize neural activity associated with cognitive function.
Free-form acquisition of shape and appearance

This report focuses on the acquisition of shape and appearance of real objects under static illumination without the need for an elaborate calibration process or an expensive setup. Emphasis is placed on ease of use and obtaining visually pleasing results. Using recent advances in matting techniques, an opacity hull of the object is computed from an un-calibrated sequence of photographs. User interaction is limited to drawing trimaps for a small subset of the recorded photographs. These trimaps indicate which parts of the photographs represent the object, background or unknown. From these trimaps the mattes of the photographs can be extracted, and subsequently a coarse intermediate opacity hull can be computed. The opacity hull is iteratively refined by computing a trimap, and thus a matte, for the remaining photographs using the already computed mattes and the coarse intermediate opacity hull. We illustrate our method on a wide range of objects, ranging from ordinary objects and human heads to large outdoor statues.
Evolutionary Trace Residues in Noroviruses: Importance in Receptor Binding, Antigenicity, Virion Assembly, and Strain Diversity

ABSTRACT Noroviruses cause major epidemic gastroenteritis in humans. A large number of strains of these single-stranded RNA viruses have been reported. Due to the absence of infectious clones of noroviruses and the high sequence variability in their capsids, it has not been possible to identify functionally important residues in these capsids. Consequently, norovirus strain diversity is not understood on the basis of capsid functions, and the development of therapeutic compounds has been hampered. To determine functionally important residues in noroviruses, we have analyzed a number of norovirus capsid sequences in the context of the Norwalk virus capsid crystal structure by using the evolutionary trace method. This analysis has identified capsid protein residues that uniquely characterize different norovirus strains and provide new insights into capsid assembly and disassembly pathways and the strain diversity of these viruses. Such residues form specific three-dimensional clusters that may be of functional importance in noroviruses. One of these clusters includes residues known to participate in the proteolytic cleavage of these viruses at high pH. Other clusters are formed in capsid regions known to be important in the binding of antibodies to noroviruses, thereby indicating residues that may be important in the antigenicity of these viruses. The highly variable region of the capsid shows a distinct cluster whose residues may participate in norovirus-receptor interactions.
Examining Expenditure Patterns of Young Single Adults in a Historical Context : Two Recent Generations Compared

F or many Americans, the age of 21 is a major point of demarcation in one's life cycle. This age marks the start of full legal adulthood—that is, the age at which the young person is no longer considered a minor and can freely engage in all legal activities, such as renting or purchasing a home. By age 21, many Americans have completed their formal education, and many more will do so during their twenties. 1 In addition, numerous individuals in this age group are starting on their first jobs leading to a career, and consequently, they face many new challenges. Achieving and maintaining financial independence can be difficult and has long-term ramifications for young adults and others in society. After all, income and spending patterns established in youth will affect one's ability not only to save for the purchase of a home, provide for a family—including future children's education—and live well in retirement, but also to contribute toward programs such as Social Security for current re-tirees. Clearly, then, understanding the economic status of young single adults is important for society as a whole, especially when substantial structural changes in the economy occur, as they have during the last generation. Indeed, the changes that have taken place may lead to outcomes that differ from what has happened in the past. On the one hand, there has been a persistent belief, based on experience, that the current generation of Americans will be better off economically than 1 According to data from the 1998 Current Population Survey (CPS), 36 percent of 21-year-olds reported graduating from high school as the highest level of education attained, while 7 percent reported completing an associate's degree or higher. Eight years later, in 2006, the CPS indicated that 28 percent of 29-year-olds reported graduating from high school as the highest level of education attained, while 41 percent reported completing an associate's degree or higher level of education. In comparison, that same year, 31 percent of 21-year-olds reported graduating from high school as the highest level of education attained, while 9 percent reported completing an associate's degree or higher level of education. is the last year for which tables showing educational attainment by exact age were produced. ) an example of the changing economic status of young single adults, see Geoffrey Paulin and Brian Riordon, " Making it on their own: the baby boom meets Generation X, " Monthly
HUMAN FACTORS CHALLENGE IN ENTREPRENEURSHIP DEVELOPMENT: AN EXPLORATIVE STUDY IN A DEVELOPING ECONOMY CONTEXT

This study explored the barriers to entrepreneurial development in Ghana with the aim of building a knowledge base for successful entrepreneurship development initiatives in a developing economy context. An exploratory approach was used with both retrospective and qualitative data collected through a survey. The results showed that the functionalities of the numerous schemes initiated to support individual entrepreneurs‟ growth were constrained due to the inherent constraints in the design of the guiding frameworks for such schemes. The study also showed that the several policies and structures initiated differently by various governments since Ghana‟s independence in March 1959 could not help enhance entrepreneurial development, because the entrepreneurial environment created for entrepreneurship development was not very friendly to the individual entrepreneurs, By implication, the study provides learning on the need to bridge the distance that exist between the designers/implementers of entrepreneurship development policies/frameworks and the individual entrepreneurs (humans).
Feature Extraction and Clustering of Croatian News Sources

This paper presents the design of a system for feature extraction and classification of news articles from Croatian news sources. An overview of supervised and unsupervised text classification and clustering machine learning techniques is presented. The techniques described are those most widely used for text classification tasks. The paper discusses a number of issues particular to text classification of the news source material, from its collection and organization to particular problems related to the evaluation of method correctness and categorization efficiency on Croatian news documents. Uses of these techniques are discussed and a proposal for their quantitative evaluation over a newly developed testing news corpus is proposed.
Phytochemical analysis of hydroethanolic extract of Turnera diffusa Willd and evaluation of its effects on astrocyte cell death

ABSTRACT Objective To evaluate the phytochemical composition of hydroethanolic extracts from powdered aerial parts of Turnera diffusa Willd (Turneraceae; T. diffusa), as well as its toxicity in astrocytes. Methods Chemical analyses of hydroethanolic extract from powdered aerial parts of T. diffusa were carried out using HPLC-DAD-ESI-MS/MS. In vitro assays using astrocytes culture were performed to evaluate cell death. Results Flavone-C, O-diglycosides, such as, luteolin-8-C-[6-deoxy-2-O-rhamnosyl]-xylo-hexos-3-uloside, apigenin-8-C-[6-deoxy-2-O-rhamnosyl]-xylo-hexos-3-uloside and apigenin-7-O-6”-p-coumaroylglucoside were the main compounds found in this hydroethanolic extract. Concentration time-effect demonstrated the toxicity of this extract at a concentration of 1,000µg/mL in astrocyte culture, after 6 and 24 hours of incubation. Conclusion In phytochemical analyses, important antioxidants (mainly flavonoids) were observed. T. diffusa extracts presented cytotoxic effect in high concentrations, leading to increased cell death in astrocyte culture.
From “First in Family” to “First to Finish”: Does College Graduation Vary by How First-Generation College Status Is Defined?

The purpose of our study was to examine the relationship between alternative definitions of first-generation college students (FGCSs) and graduation from 2- and 4-year colleges. Using Education Longitudinal Study of 2002 data, we constructed eight definitions of FGCSs based on parents’ highest level of education and the number of parents at that level. We identified a series of regression models to explain whether the student earned a 2- or 4-year degree, and focused on the association between different definitions of FGCSs and student success. We estimated both unconditional models for all 10th graders in the sample as well as conditional models for only those who enrolled in college, to see if FGCS status mattered even for those who overcame the access hurdle. Furthermore, we examined the relationship between FGCSs and the pathways to college completion for students who have initially enrolled in a 2- versus 4-year colleges.
Pragmatic-based Ontology Design and Alignment

A multitude of research works and surveys dealing with ontology reuse point to a discrepancy between ontology engineers and users when interpreting the meaning of ontology concepts. Missing the engineers’ knowledge of the concepts’ usage in certain contexts may lead to problems (e.g., pragmatic heterogeneity) in the interpretation task caused by the lack of the users’ capability to comprehend design decisions (i.e., what they have in mind when describing a domain of interest). The intended use of concepts has a great impact on their interpretation. Therefore, we assume that meaning interpretation involves more than merely identifying the semantics of assumptions explicitly expressed by model theory-based techniques, since meaning depends on both semantics and pragmatics. For this purpose, we introduce a pragmatic-based approach for implementing an evidence-based (unidirectional) communication model from engineers to users, which is mainly influenced by the relevance-based inferential model of verbal communication.
From Quantum Optics to Non-Commutative Geometry : A Non-Commutative Version of the Hopf Bundle, Veronese Mapping and Spin Representation

In this paper we construct a non-commutative version of the Hopf bundle by making use of Jaynes-Commings model and so-called Quantum Diagonalization Method. The bundle has a kind of Dirac strings. However, they appear in only states containing the ground one (${\cal F}\times \{\ket{0}\} \cup \{\ket{0}\}\times {\cal F} \subset {\cal F}\times {\cal F}$) and don't appear in remaining excited states. This means that classical singularities are not universal in the process of non-commutativization. Based on this construction we moreover give a non-commutative version of both the Veronese mapping which is the mapping from $\fukuso P^{1}$ to $\fukuso P^{n}$ with mapping degree $n$ and the spin representation of the group SU(2). We also present some challenging problems concerning how classical (beautiful) properties can be extended to the non-commutative case.
Flight test of flight control performance for airplane mode of Smart UAV

Flight test results of flight control performance of Smart UAV were described. Flight test in airplane mode was performed by internal pilot using automatic functions including auto take-off and landing, speed/altitude/heading hold as well as a point navigation and a preprogram mode. It reached to the designed maximum speed at operational altitude. The rotor speed in airplane mode was reduced to 82% from 98% RPM in order to increase rotor efficiency with reducing Mach number at tip of rotors. Rotor governor was designed to maintain dual variable rotor speed in the flight control law. The performance of flight control including speed, altitude, heading error as well as damping and frequency were evaluated in all flight envelope in the airplane mode. These control laws were modified to meet the design requirement of Smart UAV. This paper presents the flight test result of airplane mode of Smart UAV. Detailed test plan and the flight control performance were also described.
Sea ice thickness retrieval from SMOS brightness temperatures during the Arctic freeze‐up period

The Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) on board the European Space Agency's (ESA) Soil Moisture and Ocean Salinity (SMOS) mission for the first time measures globally Earth's radiation at a frequency of 1.4 GHz (L‐band). It had been hypothesized that L‐band radiometry can be used to measure the sea ice thickness due to the large penetration depth in the sea ice medium. We demonstrate the potential of SMOS to derive the thickness of thin sea ice for the Arctic freeze‐up period using a novel retrieval algorithm based on Level 1C brightness temperatures. The SMOS ice thickness product is compared with an ice growth model and independent sea ice thickness estimates from MODIS thermal infrared imagery. The ice thickness derived from SMOS is highly consistent with the temporal development of the growth simulation and agrees with the ice thickness from MODIS images with 10 cm standard deviation. The results confirm that SMOS can be used to retrieve sea ice thickness up to half a meter under ideal cold conditions with surface air temperatures below −10°C and high‐concentration sea ice coverage.
On asymptotics of eigenvectors of large sample covariance matrix

Let {X ij }, i, j = . , be a double array of i.i. d. complex random variables with EX 11 = 0, E|X 11 | 2 = 1 and E|X 11 | 4 <∞, and let An = (1 N T 1/2 n X n X* n (T 1/2 n , where T 1/2 n is the square root of a nonnegative definite matrix T n and X n is the n x N matrix of the upper-left comer of the double array. The matrix An can be considered as a sample covariance matrix of an i.i. d. sample from a population with mean zero and covariance matrix T n , or as a multivariate F matrix if T n is the inverse of another sample covariance matrix. To investigate the limiting behavior of the eigenvectors of An, a new form of empirical spectral distribution is defined with weights defined by eigenvectors and it is then shown that this has the same limiting spectral distribution as the empirical spectral distribution defined by equal weights. Moreover, if { X ij } and T n are either real or complex and some additional moment assumptions are made then linear spectral statistics defined by the eigenvectors of An are proved to have Gaussian limits, which suggests that the eigenvector matrix of An is nearly Haar distributed when T n is a multiple of the identity matrix, an easy consequence for a Wishart matrix.
A Novel Resource Scheduling Approach in Container Based Clouds

Cloud computing is a new paradigm to deliver computing resources to customers in a pay-as-you-go model. In this paper, the recently emerged container-based virtualization technology is adopted for building the infrastructure of a cloud data center. Cloud providers are concerned with the resource usage in a multi-type resource sharing environment while cloud customers desire higher quality of services. According to this, we propose a resource scheduling approach for the container virtualized cloud environments to reduce response time of customers' jobs and improve providers' resource utilization rate. The stable matching theory is applied to generate an optimal mapping from containers to physical servers. Simulations are implemented to evaluate our resource scheduling approach. The results show that our approach achieves a better performance for customers and maximal profits for cloud providers by improving the resource utilization.
Computers in Human Behavior

Robotic devices for older adults are becoming a reality. New robots are being introduced for the growing sub-population of healthy older adults, with an emphasis on supporting the positive aspects of aging. In order to inform the design and implementation of such robots, the relevant needs and concerns of this population should be studied, mapped, and translated into recommendations. We present a qualitative study of thirty cognitively-intact older adults, evaluating their attitudes and emotional reactions towards di ﬀ erent types of home robotic devices. Interview analysis of participants reactions to videos of six devices uncovered four user needs that can be threatened by the introduction of home robots: the need for independence, the need for control, the fear of being replaced, and the need for authenticity. Furthermore, results reveal that cognitively-intact older adults are willing to adopt robotic devices into their homes, contingent upon their preferences and concerns being addressed. We provide recommendations regarding how researchers and designers of home robots can better address the user needs of healthy older adults by leveraging aspects of the robot's function, speech, appearance, size, proactivity, and mobility.
Re-Active Learning: Active Learning with Relabeling

Active learning seeks to train the best classifier at the lowest annotation cost by intelligently picking the best examples to label. Traditional algorithms assume there is a single annotator and disregard the possibility of requesting additional independent annotations for a previously labeled example. However, relabeling examples is important, because all annotators make mistakes — especially crowdsourced workers, who have become a common source of training data. This paper seeks to understand the difference in marginal value between decreasing the noise of the training set via relabeling and increasing the size and diversity of the (noisier) training set by labeling new examples. We use the term re-active learning to denote this generalization of active learning. We show how traditional active learning methods perform poorly at re-active learning, present new algorithms designed for this important problem, formally characterize their behavior, and empirically show that our methods effectively make this tradeoff.
The Strategic Impacts of a Success CEO

Our main result is: in earlier stages, A CEO with more successful experiences can take advantage of the rival's incomplete learning about the depth of reasoning and take an action one step further best responding to the rival's action. Once the learning process reaches kmax (δ0-i), a more experienced player will be the same as a player with no experience, thus possibly being defeated by such an inexperienced player. We discuss three extensions of the basic model. First, since a CEO may serve different companies with different characters, we add in a variable to denote the firm's characteristic and discuss the impact on the learning process. Second, we consider the impact of limited memory on the learning of reasoning levels. Finally, we address the case of JC Penny case where Ron Johnson simply copied the past successful action.
Some Implications of a Quartic Loss Function

Motivated by a central banker with a symmetric but non-quadratic loss function, we show in this note that the approximations of two plausible loss functions of this type will include a quartic term. For skewed distributions, we establish that such a loss function implies a systematic inflation bias even when the bank targets the natural rate. Moreover, we show that the weights in an optimal combination of forecasts will differ from that under quadratic loss. We illustrate these differences using simulated data and data from the Livingston Surveys of Professional Forecasters.
Adaptive backstepping and MEMS force sensor for an MRI-guided microrobot in the vasculature

A microrobot consisting of a polymer binded aggregate of ferromagnetic particles is controlled using a Magnetic Resonance Imaging (MRI) device in order to achieve targeted therapy. The primary contribution of this paper is the design of an adaptive backstepping controller coupled with a high gain observer based on a nonlinear model of a microrobot in a blood vessel. This work is motivated by the difficulty in accurately determining many biological parameters, which can result in parametric uncertainties to which model-based approaches are highly sensitive. We show that the most sensitive parameter, magnetization of the microrobot, can be measured using a Micro-Electro-Mechanical Systems (MEMS) force sensor, while the second one, the dielectric constant of blood, can be estimated on line. The efficacy of this approach is illustrated by simulation results.