Miracle-dz/UniFAR-FTUs huggingface dataset:
Geriatric Depression and Cognitive Impairment: A Follow up Study

Introduction: Depression in older adults has become a major problem for public health. A high percentage of this population is under-diagnosed in primary care. The objectives of this work were firstly, to investigate the causes, risk factors, cognitive profile, functional status and quality of life of patients with geriatric depression, and secondly, to make a follow up of these patients. Materials and methods: Patients who consulted for memory problems associated with depression were recruited during the years 2005-2007. A semi-structured neuropsychiatric interview, an extensive neuropsychological battery, and complementary studies were performed. Results: One hundred and one depressive patients and 25 normal controls were evaluated. There was a significant prevalence and incidence of depression in the geriatric population. Significant differences (p<0.05) were found between depressive patients and controls in dyslipidemia, heart disease, cerebrovascular disease, inadequate family support, family history of depression and inactivity (OR 6.5). A global cognitive impairment was frequently associated with depression. Depression caused an alteration in functional status. Follow up results: From the 101 patients evaluated only 61 attended to the follow up visit (61.4%). All patients were indicated antidepressant treatment. Of these, only 36 patients continue with the treatment indicated in the baseline visit. Of the patients who were in antidepressant treatment (n=36) 46.6% had an excellent to good response, and 13.3% had a response from fair to poor. The main causes of poor response were adverse effects, low-dose and treatment neglect. Of the reevaluated patients, 56.6% improved in cognition or mood. The greatest improvement was observed in depression and anxiety affective symptoms. Within the cognitive profile, memory and attention trend to improve with medical treatment. Conclusion: Depression is a prevalent disease in the elderly population. It is important to implement health policies to inform the community, prevent associated risk factors, and promote appropriate treatments and rehabilitation. This condition not only affects the patient but also their environment.
A constant modulus array for real signals

A modified Constant Modulus Algorithm (CMA) is proposed for real signals impinging upon an array. The algorithm solves the mix-up problem of CMA which occurs when real signals propagate through complex channels. Moreover, it decreases computational complexity and extends the maximum number of real sources which can be resolved by a given array. Simulations are presented to support the analysis.
A monoclonal antibody that recognizes a phosphorylated epitope stains lampbrush chromosome loops and small granules in the amphibian germinal vesicle

An mAb library was produced against proteins from the germinal vesicle (GV) of the frog Xenopus laevis; mAb 104 was selected from this library on the basis of its immunofluorescent staining of lampbrush chromosome loops. Chromosomes from several species of frogs and salamanders stained equally well. The antibody also stained the surface of numerous small granules in the GV nucleoplasm. The interior of the same granules was stained by antibodies against small nuclear ribonucleoproteins (snRNPs). mAb 104 also stained somatic nuclei from many vertebrate and invertebrate species, usually in a finely punctate pattern similar to that described for anti-snRNP and other antinuclear antibodies. The staining of somatic nuclei was much stronger during the mitotic stages than during interphase. Immunoblot analysis showed that mAb 104 recognizes a phosphorylated epitope.
Towards a socially aware home router

Effective security on home wireless networks remains an elusive goal. The most prevalent method uses a single pre-shared key to enforce access control, but the requirement for convenience often results in poorly chosen keys which rarely change over time. Furthermore, since there is no way to maintain control of the key once it is distributed, there is no way to know who is actually on the network. Methods already exist which provide better security (e.g. EAP-TLS), but few users have the knowledge or experience to deploy them. We propose a new paradigm which brings access control to the average user's level. Our idea is to leverage online social networks to identify relationships between the owner of a home wireless network and its potential users. Rather than being responsible for the distribution and control of a single all-powerful key, the wireless owner simply declares the set of users and relationships which they trust to access their network. From the perspective of the wireless user, authentication is as simple as logging into the online social networking service like normal.
Potential liabilities: Social investment policy as biopolitics in New Zealand – An examination of the National Coalition government’s welfare policies

Using Michel Foucault’s theories of biopolitics, about risk and security, I examine the welfare policies of the National Coalition Government in New Zealand (2008–2017). This government attempted to mitigate risk by projecting possible challenges and solutions to ‘vulnerable populations’. Welfare was re-defined in monetarist economic terms, as ways to ensure ‘small government’. Over the three terms of government they brought in changes across the education, and social services, with the intent of implementing new economic facets to reduce the cost to the state of beneficiaries and their dependent children. Using cross-ministry data collection, they planned to identify the ‘job-shy’ parents and children deemed ‘vulnerable’. Social Investment aimed to change the behaviours of such populations, whom the National Coalition government deemed future potential liabilities for the state. Projecting costs over 20 or 30 years and modelling the costs of dysfunction would give the social agencies improved information. Early intervention would save the state welfare budget, and responsibilize the young children at risk of themselves becoming beneficiaries later in life.
terkait: semantic interactions with web content

We present our ongoing development of an application, called terkait - that supports a user with related information while browsing the web. terkait analyses semantic objects that are either annotated directly in the content or retrieved by external services. The extracted entities are then preprocessed, filtered and finally presented to the user in a non-obtrusive user interface. The user can then choose to learn more about certain knowledge objects by browsing the related content that is presented alongside the particular entity. The architecture is implemented with clean and open APIs to allow different services to be used for both, the analyzing part as well as the querying for related content.
Breast cancer detection using a hybrid Finite difference frequency domain and particle swarm optimization techniques

A hybrid technique based on finite-difference frequency domain and particle swarm optimization techniques is proposed to reconstruct the breast cancer cell dimension and determines its position. Finite-difference frequency domain is formulated to calculate the scattered field after illuminating the breast by a microwave transmitter. Two-dimensional and three- dimensional models for the breast are used. The models include randomly distributed fatty breast tissue, glandular tissue, 2-mm thick skin, as well as chest wall tissue. The models are characterized by the dielectric properties of the normal breast tissue and malignant tissue at 800 MHz. Computer simulations have been performed by means of a numerical program; results show the capabilities of the proposed approach.
A robot with style, because you are worth it!

Research in social human-robot interaction gets more and more of its inspiration from psychology to make robots' behaviour more socially acceptable when among humans. In the context of rendering a robot more suitable to be a companion for children, we propose different parenting styles (namely authoritative and permissive) and evaluate them. As a first step, we use expression cues of the parenting styles; we implemented behaviours of different styles played out by two robots, Nao and Reeti, with body and facial channels respectively for communication. 88 parents watched videos of the robots and replied to a questionnaire about the authoritativeness of the robots. The results showed that the styles were perceptible through the non-verbal behaviours of the robots. The dominant condition was perceived to be more authoritative than the less dominant condition, which validates the hypothesis. We also notice an effect of the robot's modality of expressions; further work should confirm hypotheses on the modality's effects of the perception on authoritativeness of the robot.
Acoustic-to-articulatory inversion using an episodic memory

This paper presents a new acoustic-to-articulatory inversion method-based on an episodic memory, which is an interesting model for two reasons. First, it does not rely on any assumptions about the mapping function but rather it relies on real synchronized acoustic and articulatory data streams. Second, the memory structurally embeds the naturalness of the articulatory dynamics. In addition, we introduce the concept of generative episodic memory, which enables the production of unseen articulatory trajectories according to the acoustic signals to be inverted. The proposed memory is evaluated on the MOCHA corpus. The results show its effectiveness and are very encouraging since they are comparable to those of recently proposed methods.
Sn Addition on Se 80 Te 20-x Sn x Glass Alloys, Theoretically Prediction and Experimental Optical Properties of Thin Films

The present article is divided to two parts, the theoretical part study the effect on the physical properties such as average coordination number and fraction of floppy modes with the variation in tin content for Se80Te20-xSnx (x=6, 9, 12, and 15 at.%) glassy alloys. We show that, by taking more Sn content in Se80Te20-xSnx (x=6, 9, 12, and 15 at.%) glassy alloys, it reduces the fraction of floppy modes. The experimental part study the optical properties of ternary glassy of Se80Te20-xSnx (x=6, 9, 12, and 15 at.%) thin films. These thin films of Se80Te20-xSnx (x=6, 9, 12, and 15 at.%) were prepared by the conventional thermal evaporation technique on glass substrate. Optical reflection and transmission spectra of Se80Te20-xSnx (x=6, 9, 12, and 15 at.%) chalcogenide thin films have been obtained in the range 200−2500 nm at room temperature. The absorption coefficient (α) has been determined as a function of Sn content. It was found that the optical band gap decrease with increasing the Sn content. The results are interpreted in terms of the change in concentration of localized states due to the shift in Fermi level as a result of varying of Sn content.
Signaling from Blood Vessels to CNS Axons through Nitric Oxide

Brain function is usually perceived as being performed by neurons with the support of glial cells, the network of blood vessels situated nearby serving simply to provide nutrient and to dispose of metabolic waste. Revising this view, we find from experiments on a rodent central white matter tract (the optic nerve) in vitro that microvascular endothelial cells signal persistently to axons using nitric oxide (NO) derived from the endothelial NO synthase (eNOS). The endogenous NO acts to stimulate guanylyl cyclase-coupled NO receptors in the axons, leading to a raised cGMP level which then causes membrane depolarization, apparently by directly engaging hyperpolarization-activated cyclic nucleotide-gated ion channels. The tonic depolarization and associated endogenous NO-dependent cGMP generation was absent in optic nerves from mice lacking eNOS, although such nerves responded to exogenous NO, with raised cGMP generation in the axons and associated depolarization. In addition to the tonic activity, exposure of optic nerves to bradykinin, a classical stimulator of eNOS in endothelial cells, elicited reversible NO- and cGMP-dependent depolarization through activation of bradykinin B2 receptors, to which eNOS is physically complexed. No contribution of other NO synthase isoforms to either the action of bradykinin or the continuous ambient NO level could be detected. The results suggest that microvascular endothelial cells participate in signal processing in the brain and can do so by generating both tonic and phasic NO signals.
EE 04025-Notes on Linear Model Predictive Control

Linear model predictive control (MPC) assumes a linear system model, that the constraints sets are representable via linear inequalities and that the objective function is convex quadratic. Linear MPC is appealing because the associated optimisation problem typically solved at each time interval may be expressed as a convex quadratic program, which can be solved efficiently online. Topics not covered include methods for solving quadratic programs, soft constraints, terminal state constraints, closed-loop stability, closed-loop robustness and optimal reference trajectory calculation. A Matlab simulation example is included for illustration.
Lexico-syntactic and Semantic Patterns for Extracting Knowledge from Persian Texts

—In recent years, knowledge extraction from texts is focused to overcome to bottleneck of building ontologies for semantic web. Pattern based, template driven and linguistic methods are among the successful approaches to extract ontological knowledge from raw texts. This paper introduces some lexico-syntactic and semantic patterns and templates for extracting conceptual knowledge from Persian texts. The described patterns are general and domain/ application independent and work at sentence level. They are used to extract taxonomic and non-taxonomic relations and axioms from phrases and sentences. Among the introduced patterns and templates, semantic patterns are language independent and although linguistic (lexico-syntactic) patterns are introduced for Persian language, they could easily be adopted to other languages such as English. This paper will first have a brief overview on linguistic and template driven methods to discover ontological knowledge from texts. Then the templates for Persian simple sentences will be introduced. The extracted relations may be hyponymy, meronymy, attribute/value, part-of, equivalency, etc. The introduced templates exploit semantic information to not only extract the instances of predefined relations (the concepts related by them), but also define new relations. In each case some examples of the experimental results will make the patterns clear.
Integrated Codesign of Printable Robots

This work presents a system by which users can easily create printable origami-inspired robots from high-level structural speciﬁcations. Starting from a library of basic mechanical, electrical, and software building blocks, users can hierarchically assemble integrated electromechanical components and programmed mechanisms. The system compiles those designs to cogenerate complete fabricable outputs: mechanical drawings suitable for direct manufacture, wiring instructions for electronic devices, and ﬁrmware and user interface (UI) software to control the ﬁnal robot autonomously or from human input. This process allows everyday users to create on-demand custom printable robots for personal use, without the requisite engineering background, design tools, and cycle time typical of the process today. This paper describes the system and its use, demonstrating its abilities and versatility through the design of several disparate robots. [DOI: 10.1115/1.4029496]
Prediction of performance anomalies in web-applications based-on software aging scenarios

The topic of this paper is about prediction of performance anomalies caused by software aging. We have developed a framework for detection of performance anomalies that is targeted to web and component-based applications. In this study, we selected some amount of historical data previously collected and we conducted a correlation analysis with this data. The resulting dataset was then submitted to some Machine-Learning (ML) classification algorithms. The best algorithms were selected according to the accuracy and precision. In a second step, we induced some synthetic aging scenarios (memory leaks and CPU contention) in the application and we tried to do estimation of the system parameters by using time-series analysis. With the estimated values we conducted a classification with the three previous ML algorithms. From the initial results we observed that combining the estimation of parameters supported by time-series models with ML classification techniques provides some good results on the prediction of performance anomalies. We also observed that there is no single ML algorithm that can be applied effectively to predict the response time for all the web-transactions.
Far-field continuous speech recognition system based on speaker Localization and sub-band Beamforming

This paper proposes a distant speech recognition system based on a novel speaker localization and beamforming (SRLB) algorithm. To localize the speaker an algorithm based on steered response power by utilizing harmonic structures of speech signal is proposed. This new scheme has the ability of speaker verification by fundamental frequency variation; therefore it can be utilized in the design of a speech recognition system for verified speakers. Then the performance of the Farsi speech recognition engine is evaluated under notorious conditions of noise and reverberation. Simulation results and tests on real data shows that by utilizing proposed localization scheme, recognition accuracy improves by 28% in high noise and reverberant conditions compared to the accuracy of single channel recognition. The capability of this algorithm in localizing a verified speaker improves system robustness to speech noises and reduces recognition errors up to %52 in the presence of speech noise.
RFPL3 and CBP synergistically upregulate hTERT activity and promote lung cancer growth

hTERT is the key component of telomerase and its overactivation contributes to maintaining telomere length and cell immortalization. Previously, we identified RFPL3 as a new transcription activator of hTERT in lung cancers. However, the exact mechanism of RFPL3 in mediating hTERT activation and its associated signal regulatory network remain unclear. In this study, we found that RFPL3 colocalized and interacted directly with CBP in the nucleus of lung cancer cells. Immunohistochemical analysis of tissue microarrays of lung cancers revealed the simultaneous overexpression of both RFPL3 and CBP predicted relatively poor prognosis. Furthermore, we confirmed their synergistic stimulation on hTERT expression and tumor cell growth. The binding of RFPL3 to hTERT promoter was reduced markedly when CBP was knocked down by its specific siRNA or suppressed by its inhibitor in lung cancer cells with stable overexpression of RFPL3. When one of the two proteins RFPL3 and CBP was upregulated or downregulated, whereas the another remains unchanged, hTERT expression and telomerase activity were activated or repressed accordingly. In the meantime, the growth of lung cancer cells was also promoted or attenuated accordingly. Furthermore, we also found that RFPL3 coordinated with CBP to upregulate hTERT through the CBP-induced acetylation of RFPL3 protein and their co-anchoring at hTERT promoter region. Collectively, our results reveal a new mechanism of hTERT regulation in lung cancer cells and suggest the RFPL3/CBP/hTERT signaling pathway may be a new targets for lung cancer treatment.
Self-Confidence and Unraveling in Matching Markets

We document experimentally how biased self-assessments affect the outcome of matching markets. In the experiments, we exogenously manipulate the self-confidence of participants regarding their relative performance by employing hard and easy real-effort tasks. We give participants the option to accept early offers when information about their performance has not been revealed, or to wait for the assortative matching based on their actual relative performance. Early offers are accepted more often when the task is hard than when it is easy. We show that the treatment effect works through a shift in beliefs, i.e., underconfident agents are more likely to accept early offers than overconfident agents. The experiment identifies a behavioral determinant of unraveling, namely biased self-assessments, which can lead to penalties for underconfident individuals as well as efficiency losses.
Tuning Continual Exploration in Reinforcement Learning

This paper presents a model allowing to tune continual exploration in an optimal way by integrating exploration and exploitation in a common framework. It first quantifies exploration by defining the degree of exploration of a state as the entropy of the probability distribution for choosing an admissible action. Then, the exploration/exploitation tradeoff is formulated as a global optimization problem: find the exploration strategy that minimizes the expected cumulated cost, while maintaining fixed degrees of exploration at the states. In other words, exploitation is maximized for constant exploration. This formulation leads to a set of nonlinear iterative equations reminiscent of the value-iteration algorithm. Their convergence to a local minimum can be proved for a stationary environment. Interestingly, in the deterministic case, when there is no exploration, these equations reduce to the Bellman equations for finding the shortest path. If the graph of states is directed and acyclic, the nonlinear equations can easily be solved by a single backward pass from the destination state. Stochastic shortest-path problems and discounted problems are also examined, and they are compared to the SARSA algorithm. The theoretical results are confirmed by simple simulations showing that the proposed exploration strategy outperforms the ǫ-greedy and the naive Boltzmann strategies.
DOA estimation for wideband signals via the Homotopy approach

Compared with the conventional subspace-based methods, direction-of-arrival (DOA) estimation from the sparse recovery perspective renders higher resolution capability and lower data requirement. When wideband signals are handled, however, straightforward adoption of such an idea is no longer reasonable, due to the diversity of estimation at each frequency bin. In this paper, we address the problem of DOA estimation for wideband signals according to the weighted subspace fitting (WSF) criterion, which is solved by the Homotopy method. The proposed algorithm holistically exploits the joint sparsity feature embedded in and among multiple frequency bins, and does not require any difficult selection of hyperparameters. Simulation results illustrate the superior performance achieved in the proposed algorithm.
g-H 2 AX Dephosphorylation by Protein Phosphatase 2 A Facilitates DNA Double-Strand Break Repair

Dipanjan Chowdhury, Michael-Christopher Keogh, Haruhiko Ishii, Craig L. Peterson, Stephen Buratowski, and Judy Lieberman* CBR Institute for Biomedical Research and The Department of Pediatrics Harvard Medical School Boston, Massachusetts 02115 Department of Biological Chemistry and Molecular Pharmacology Harvard Medical School Boston, Massachusetts 02115 Program in Molecular Medicine University of Massachusetts Medical School Worcester, Massachusetts 01655