Miracle-dz/UniFAR-FTUs huggingface dataset:
Active global localization for a mobile robot using multiple hypothesis tracking

We present a probabilistic approach for mobile robot localization using an incomplete topological world model. The method, called the multi-hypothesis localization (MHL), uses multi-hypothesis Kalman filter based pose tracking combined with a probabilistic formulation of hypothesis correctness to generate and track Gaussian pose hypotheses online. Apart from a lower computational complexity, this approach has the advantage over traditional grid based methods that incomplete and topological world model information can be utilized. Furthermore, the method generates movement commands for the platform to enhance the gathering of information for the pose estimation process. Extensive experiments are presented from two different environments, a typical office environment and an old hospital building.
Interim Report for Final Year Project Deep Learning for Text Classification in Azure Infrastructure

The emerging deep learning technologies and trending of big data have enabled many research studies as well as applications of natural language processing (NLP). However, deep learning NLP models for Chinese processing are still underdeveloped. Inspired by the potential of Chinese NLP with deep learning, this project aims at exploring and developing different deep learning models that can classify short Chinese sentences according to their underlying sentiments. Cooperating with Microsoft, this project has already designed, implemented, and evaluated two deep learning models, namely Forward-LSTM and Bi-LSTM, which leverage recurrent neural networks to capture high-level semantics of natural languages. Experiments on a large real-world dataset showed that LSTM networks performed remarkably when classifying two labels, reaching an average accuracy of 95%. However, the Bi-LSTM model only gave an accuracy of 60% when classifying five labels. In later stages of this project, further investigations of LSTM networks will be conducted to improve the performance. Possible directions include introducing an “unknown” token in the datasets, and adopting other loss functions. In addition, new deep learning networks such as CNNs will also be explored and evaluated.
Evaluating Roles of Nodes in Optimal Allocation of Vaccines with Economic Considerations

Since the allocation of vaccines is often constrained by limited resources, designing an economical vaccination strategy is a fundamental goal of the epidemiological modelling. In this study, with the objective of reducing costs, we determine the optimal allocation of vaccines for a general class of infectious diseases that spread mainly via contact. We use an optimization routine to identify the roles of nodes with distinct degrees as depending on the cost of treatment to that of vaccination (relative cost of treatment). The optimal allocation drives vaccination priority to medium-degree nodes at a low relative cost of treatment or to high-degree nodes at a high relative cost of treatment. According to the presented results, we may adjust the vaccination priority in the face of an endemic situation.
A Fast and Personalized Biomechanical Model Resume

The purpose of the project is to develop methods and a biomechanical model for virtual testing of fit and interaction of virtual components directly from a Computer Aided Design (CAD) system, specifically for the hearing aid industry. We propose to develop an adaptable biomechanical model and fast methods for physical simulation including contact forces for insertion of the virtual components. This will decrease the time-to-market and improve hearing aid quality. The technology developed will be transferrable to other applications e.g. surgical simulation and medical devices. Project description
Change-link 2.0: a digital forensic tool for visualizing changes to shadow volume data

We present Change Link 2.0, a coordinated and multiple view tool for digital forensics which supports an understanding of how shadow volume data have changed over time. An improvement over the original Change-Link tool [25], Change-Link 2.0 provides an overview, a directory-tree view, a directory content view, and a metadata view in a side-by-side, split-screen, linked-view interface that supports easy browsing and detection of files and directories that have changed over time. This data visualization approach supports faster comprehension of digital forensic data, quick detection of anomalous data, and a better understanding of "what happened? " Input to Change-Link 2.0 is an evidentiary hard drive containing multiple versions of files and directories which have been archived by the Microsoft Volume Shadow Copy Service [28]. Our contributions include data visualization techniques that support an overview of the entire dataset, as well as an understanding of how the directory-tree structure, individual directory content, and file and directory metadata have changed over time. Change-Link 2.0, and its predecessor, are the first data visualization tools that we are aware of which support the forensic examination of shadow volume data.
Dynamic facial emotion recognition from 4D video sequences

Emotions are characterized as responses to internal and external events of a person. Emotion recognition through facial expressions from videos plays a vital role in human computer interaction where the dynamic changes in face movements needs to be realized quickly. In this work, we propose a simple method, using the geometrical based approach for the recognition of six basic emotions in video sequences of BU-4DFE database. We have chosen optimum feature points out of the 83 feature points provided in the BU-4DFE database. A video expressing emotion will have frames containing neutral, onset, apex and offset of that emotion. We have dynamically identified the frame that is most expressive for an emotion (apex). The Euclidean distance between the feature points in apex and neutral frame is determined and their difference in corresponding neutral and the apex frame is calculated to form the feature vector. The feature vectors thus formed for all the emotions and subjects are given to Neural Networks (NN) and Support Vector Machine (SVM) with different kernels for classification. We have compared the accuracy obtained by NN & SVM. Our proposed method is simple, uses only two frames and yields good accuracy for BU-4DFE database. Very complex algorithms exist in literature using BU-4DFE database and our proposed simple method gives comparable results. It can be applied for real time implementation and kinesics in future.
MNAzymes, a Versatile New Class of Nucleic Acid Enzymes That Can Function as Biosensors and Molecular Switches

To increase the versatility and utility of nucleic acid enzymes, we developed multicomponent complexes, known as MNAzymes, which produce amplified “output” signals in response to specific “input” signals. Multiple oligonucleotide partzymes assemble into active MNAzymes only in the presence of an input assembly facilitator such as a target nucleic acid. Once formed, MNAzymes catalytically modify a generic substrate, generating an amplified output signal that heralds the presence of the target while leaving the target intact. We demonstrated several applications including sensitive, isothermal target detection; discrimination of polymorphisms; and highly specific monitoring of real-time polymerase chain reaction (PCR). Furthermore, we showed their capacity to function as molecular switches and to work in series to create a molecular cascade. The modular nature of MNAzymes, together with the separation of input and output functionalities, provides potential for their integration into diverse devices such as diagnostic biosensors, molecular computers, and/or nanoscale machines.
How big were the first cosmological objects

We calculate the cooling times at constant density for haloes with virial temperatures from 100 K to 1 × 105 K that originate from a 3σfluctuation of a CDM power spectrum in three different cosmologies. Our intention is to determine the first objects that can cool to low temperatures, but not to follow their dynamical evolution. We identify two generations of haloes: those with low virial temperatures, Tvir ≲ 9000 K that remain largely neutral, and those with larger virial temperatures that become ionized. The lower temperature, lower mass haloes are the first to cool to 75 per cent of their virial temperature. The precise temperature and mass of the first objects are dependent upon the molecular hydrogen (H2) cooling function and the cosmological model. The higher mass haloes collapse later but, in this paradigm, cool much more efficiently once they have done so, first via electronic transitions and then via molecular cooling: in fact, a greater residual ionization once the haloes cool below 9000 K results in an enhanced H2 production and hence a higher cooling rate at low temperatures than for the lower mass haloes, so that within our constant-density model it is the former that are the first to cool to really low temperatures. We discuss the possible significance of this result in the context of CDM models in which the shallow slope of the initial fluctuation spectrum on small scales leads to a wide range of halo masses (of differing overdensities) collapsing over a small redshift interval. This ‘crosstalk’ is sufficiently important that both high- and low-mass haloes collapse during the lifetimes of the massive stars which may be formed at these epochs. Further investigation is thus required to determine which generation of haloes plays the dominant role in early structure formation.
A FEM simulation approach for multilayered SAW delay line devices

The active compliance control is popular in surgical robots, which requires novel wireless and passive pressure sensor. In this paper, a simulation of surface acoustic wave multilayered device is presented. It includes a SiO2 / Al electrode/ YZ-LiTaO3, which has a high coupling coefficient as well as a low temperature coefficient of delay. An eigenfrequency analysis is done first to calculate the phase velocity and input frequency of the RF signal. A time domain analysis is pursued next to generate the surface acoustic waves and the characteristics of wave propagation. In this process, the boundary reflection is eliminated by adding perfectly matched layers and appropriate damping. This approach is essential for assessment of SAW pressure sensor design configurations prior to prototyping.
Characterization of Neuroprotective Effects of Biphalin, an Opioid Receptor Agonist, in a Model of Focal Brain Ischemia

Approximately 795,000 people experience a new or recurrent stroke in the United States annually. The purpose of this study was to assess the protective effect of a nonselective opioid receptor agonist, biphalin, in brain edema and infarct damage by using both in vitro and in vivo models of stroke. In an in vivo model of ischemia, biphalin significantly decreased edema (66.6 and 58.3%) and infarct (52.2 and 56.4%) ratios in mouse transient (60-min occlusion/24-h reperfusion) and permanent (6 h) middle cerebral artery occlusion models, respectively. Biphalin administration also showed decreased neurodegeneration in hippocampal, cortical, and striatal brain tissue after ischemia, evidenced by reduced Fluoro-Jade C staining. In addition, biphalin improved neurological function after stroke injury evidenced by neurological score and locomotor activity evaluation. Biphalin significantly decreased penumbral expression of Na+, K+, 2Cl− cotransporter (NKCC) and the translocation of the conventional isoforms of protein kinase C (PKC). It also reversed the activation of PKC-induced cell volume increase during ischemia in primary neuronal cell cultures exposed to 1 h of oxygen glucose deprivation. These data suggest that opioid receptor activation provides neuroprotection during stroke, and a possible explanation of this mechanism could be the inhibition of NKCC function via the regulation of PKC-dependent cell signaling.
Joint Relay Selection and Analog Network Coding Using Differential Modulation in Two-Way Relay Channels

In this paper, we consider a general bidirectional relay network with two sources and N relays when neither the source nodes nor the relays know the channel-state information (CSI). A joint relay-selection and analog-network coding using differential modulation (RS-ANC-DM) is proposed. In the proposed scheme, the two sources employ differential modulations and transmit the differential modulated symbols to all relays at the same time. The signal received at the relay is a superposition of two transmitted symbols, which we call analog network-coded symbols. Then, a single relay that has minimum-sum symbol error rate (SER) is selected out of N relays to forward the ANC signals to both sources. To facilitate the selection process, in this paper, we also propose a simple suboptimal Min-Max criterion for relay selection, where a single relay that minimizes the maximum SER of two source nodes is selected. Simulation results show that the proposed Min-Max selection has almost the same performance as the optimal selection but is much simpler. The performance of the proposed RS-ANC-DM scheme is analyzed, and a simple asymptotic SER expression is derived. The analytical results are verified through simulations.
Fuzzy Logic Networks for Speech Recognition

modeled system which is not diﬃcult to understand and which provides suitable abilities for a general task of speech recognition. Speech is a non-stationary process; our goal is to model this property using mentioned memories and fuzzy logic memories. This paper is organized as follows. The second part describes initial identiﬁcation of simple speech features in the input signal. This identiﬁcation is realized in a form of binary classiﬁers that decide whether there is a speciﬁc feature detected at the input or not. The classiﬁers are represented by fuzzy logical functions where their output’s values correspond to the level of the ﬁred feature. The third part presents a hierarchical structure of the network which is responsible for identiﬁcation of larger units of the input signal (time sequence). The fourth part describes brieﬂy inputs used for the network evaluation. The ﬁfth part describes some results and the ﬁnal part concludes this paper.
High Sensitivity C - Reactive Protein is Associated with Diastolic Dysfunction in Young African Americans without Clinically Evident Cardiac Disease

Background: Diastolic dysfunction (DD) is associated with myocardial fibrosis mediated by inflammation. Higher levels of inflammation found in African Americans (AAs) may predict DD among asymptomatic individuals. We tested the hypothesis that high sensitivity C-reactive protein (hs-CRP), a biomarker of inflammation, is associated with DD in asymptomatic AAs. Methods: We prospectively recruited 107 asymptomatic AAs without any history of cardiac, renal or inflammatory diseases or alcoholism. We measured hs-CRP and B-type Natriuretic peptide (BNP) levels and estimated left ventricular end diastolic pressure (LVEDP), mass and systolic function with echocardiography. Multivariate logistic regression analysis was used to define whether hs-CRP is an independent predictor of LVEDP. Results: Among 107 subjects: the mean age was 48±10 yrs, 58 (54%) were men, 59 (55%) had diabetes (DM), 48 (45%) had hypertension (HTN), the mean BMI was 30.5±4.8 and the mean ejection fraction was 63.1±5.8%. DD was present in 56(52%) subjects, 38 (36%) of whom also had a high LVEDP. On multivariate analysis, hs-CRP was independently associated with DD [odds ratio 3.36 (95% CI= 1.07 - 10.5, p = 0.04]. There was a 61% and 133% increase in the prevalence of any DD and DD with high LVEDP, respectively, between the lowest and the highest hs-CRP quartiles. Conclusion: Diastolic dysfunction is prevalent among asymptomatic African Americans and it is independently associated with elevated level of hs-CRP, an inflammation marker.
Approximation schemes for finding the value functions for differential games with nonterminal payoff functional

Abstract. A finite difFerence scheme for finding viscosity solutions of specificaJly stated problems for the Hamilton-Jacobi equations is proposed. Solutions of such Problems must satisfy one of two inequalities involved into the definition of viscosity solutions in the region where they are less then a given function. From the point of view of optimal control theory and the theory of differential games, these results can be applied to the finding the value functions of control problems and differential games with nonterminal payoff functioneds of a frequently used form.
A Unified Approach to Hybrid Coding

Hybrid analog-digital coding has been used for several communication scenarios, such as joint source-channel coding of Gaussian sources over Gaussian channels and relay communication over Gaussian networks. In this paper, a generalized hybrid coding technique is proposed for communication over discrete memoryless and Gaussian systems, and its utility is demonstrated via three examples-lossy joint source-channel coding over multiple access channels, channel coding over two-way relay channels, and channel coding over diamond networks. The corresponding coding schemes recover and extend several existing results in the literature.
Special Feature IP-based Mobility Management Technology

This article reviews recent progress in the study of IP-based mobility management technology for enhancing the mobility of cellular phones and other mobile nodes in fourth-generation mobile communications systems. The architecture and components of this management technology are described and some experimental and simulation results are presented. IP-based Mobility Management Technology Special Feature † NTT DoCoMo, Inc. Yokosuka-shi, 239-8536 Japan E-mail: okajimai@nttdocomo.co.jp * Handoff: The act of transferring a wireless signal from one cell site to another. Equivalent to handover.
Maternal substance use disorder, difficult temperament and child psychopathology: Examining a biopsychosocial model for the intergenerational transmission of vulnerability

MATERNAL SUBSTANCE USE DISORDER, DIFFICULT TEMPERAMENT AND CHILD PSYCHOPATHOLOGY: EXAMINING A BIOPSYCHOSOCIAL MODEL FOR THE INTERGENERATIONAL TRANSMISSION OF VULNERABILITY by Wendy Carolina Franco Advisor: Elliot Jurist, Ph.D., Ph.D. Background: Substance abuse is a significant issue that affects the lives of adults and children in our society. Children of substance abusing parents are at greater risk for poor psychosocial adjustment and psychopathology. The present study drew on biopsychosocial and epigenetic approaches to study vulnerability and resilience in children. The aim was to advance the understanding of child psychopathology and of intergenerational effects of maternal substance use disorder (SUD) by examining the independent and combined contributions of risk factors for child psychopathology in children of mothers with SUD. Employing a “goodness of fit model,” which posits that adverse child outcomes emerge as a consequence of a mismatch between endogenous child characteristics and their caregiving environment, it was hypothesized that difficult temperament and maternal SUD would represent a mismatch that would influence the presence of child behavioral problems. Method: The present study examined the relationship between maternal SUD, child psychopathology, and difficult temperament in a predominantly poor, ethnic minority sample of 147 mother and child dyads. To generate empirically sound data on substance use disorders, we used the Structured Clinical Interview for DSM-III-R/DSM-IV
Resource Allocation and Power Control for Power Minimization in OFDM Networks

We consider the problem of minimizing the total transmission power for a OFDM network where mutual interference exists among cells, with the power and load constraints for each base station (BS) and the rate demand constraint for every user. To solve the power minimization problem, we develop a distributed resource allocation and power control algorithm with low complexity. The complexity of the proposed algorithm is also analyzed. Numerical results show that the proposed algorithm is superior to the conventional schemes in terms of power consumption.
CD4 T Cells from Malaria-Nonexposed Individuals Respond to the CD36-Binding Domain of Plasmodium falciparum Erythrocyte Membrane Protein-1 via an MHC Class II-TCR-Independent Pathway1

We have studied the human CD4 T cell response to a functionally conserved domain of Plasmodium falciparum erythrocyte membrane protein-1, cysteine interdomain region-1α (CIDR-1α). Responses to CIDR-1α were striking in that both exposed and nonexposed donors responded. The IFN-γ response to CIDR-1α in the nonexposed donors was partially independent of TCR engagement of MHC class II and peptide. Contrastingly, CD4 T cell and IFN-γ responses in malaria-exposed donors were MHC class II restricted, suggesting that the CD4 T cell response to CIDR-1α in malaria semi-immune adults also has a TCR-mediated component, which may represent a memory response. Dendritic cells isolated from human peripheral blood were activated by CIDR-1α to produce IL-12, IL-10, and IL-18. IL-12 was detectable only between 6 and 12 h of culture, whereas the IL-10 continued to increase throughout the 24-h time course. These data strengthen previous observations that P. falciparum interacts directly with human dendritic cells, and suggests that the interaction between CIDR-1α and the host cell may be responsible for regulation of the CD4 T cell and cytokine responses to P. falciparum-infected erythrocytes reported previously.
Use of Smoking Cessation Methods Among Patients Receiving Office-based Buprenorphine Maintenance Treatment

Objectives: Provision of smoking-cessation treatment is limited in office-based buprenorphine maintenance treatment (BMT) settings. This study describes smoking and smoking-cessation behaviors among patients receiving office-based BMT. Methods: Cross-sectional study of patients receiving office-based BMT at a community health center in the Bronx, NY. We interviewed patients assessing sociodemographic, and substance use and tobacco use characteristics, including methods used for smoking cessation. We reported simple frequencies and explored associations of BMT characteristics with smoking behaviors. Results: Of 68 patients, 87.7% were current cigarette smokers, 7.9% were former smokers, and 4.4% had never smoked. Of lifetime smokers, 83.1% reported at least 1 prior quit attempt, and 78.5% had used medication (75.4% used nicotine replacement therapy, 29.2% varenicline, and 9.2% bupropion). Ten patients (15.4%) reported using electronic cigarettes to try to quit smoking. Stopping “cold turkey” (40.0%) and gradually decreasing the number of cigarettes smoked (32.3%) were nonpharmacological methods of quitting tried most often. Use of behavioral support, including stop-smoking programs and counseling, was low. Higher dose and longer duration of BMT was associated with greater smoking frequency. Conclusions: Patients receiving BMT have a high prevalence of cigarette smoking, though most have tried to quit, and have prior experience with pharmacotherapy for smoking cessation. Efforts to optimize smoking-cessation treatments among BMT patients are needed.