Miracle-dz/UniFAR-FTUs huggingface dataset:
Dlg1, Sec8, and Mtmr2 Regulate Membrane Homeostasis in Schwann Cell Myelination

How membrane biosynthesis and homeostasis is achieved in myelinating glia is mostly unknown. We previously reported that loss of myotubularin-related protein 2 (MTMR2) provokes autosomal recessive demyelinating Charcot–Marie–Tooth type 4B1 neuropathy, characterized by excessive redundant myelin, also known as myelin outfoldings. We generated a Mtmr2-null mouse that models the human neuropathy. We also found that, in Schwann cells, Mtmr2 interacts with Discs large 1 (Dlg1), a scaffold involved in polarized trafficking and membrane addition, whose localization in Mtmr2-null nerves is altered. We here report that, in Schwann cells, Dlg1 also interacts with kinesin 13B (kif13B) and Sec8, which are involved in vesicle transport and membrane tethering in polarized cells, respectively. Taking advantage of the Mtmr2-null mouse as a model of impaired membrane formation, we provide here the first evidence for a machinery that titrates membrane formation during myelination. We established Schwann cell/DRG neuron cocultures from Mtmr2-null mice, in which myelin outfoldings were reproduced and almost completely rescued by Mtmr2 replacement. By exploiting this in vitro model, we propose a mechanism whereby kif13B kinesin transports Dlg1 to sites of membrane remodeling where it coordinates a homeostatic control of myelination. The interaction of Dlg1 with the Sec8 exocyst component promotes membrane addition, whereas with Mtmr2, negatively regulates membrane formation. Myelin outfoldings thus arise as a consequence of the loss of negative control on the amount of membrane, which is produced during myelination.
Squishy Materials

stances they use in the kitchen and the bathroom are not simple liquids or solids. Everyone is familiar with three states of matter: solids, liquids, and gases. However, creams, shampoo, toothpaste, and ketchup all have properties of both liquids and solids. This paper describes demonstrations and laboratory exercises1 that show intriguing properties of squishy substances, defined as materials that are not unambiguously solid, liquid, or gas. Unlike some areas of physics, the concepts behind squishy materials are understandable even by beginning students. Squishy physics can be used to show physics questions arising from everyday life and to convey the excitement of current research. The activities described in this paper have two goals. The first goal is to show how complex fluids (such as sand or shaving cream) differ from simple liquids (such as water or honey). The key difference is that the effective viscosity of a complex fluid strongly depends on how it is measured. The second goal is to get students to think about how the microscopic properties of a sample relate to the macroscopic properties. We do this by exposing students to the theory of jamming2 so that they get a taste of current research not normally seen in introductory science courses. At Emory, we have incorporated the ideas in this article as a short unit within an undergraduate freshman seminar that covers several topics in science. These activities could easily be adapted for other introductory physics courses, and the treatment can be conceptual or quantitative.
Newscast EM

We propose a gossip-based distributed algorithm for Gaussian mixture learning, Newscast EM. The algorithm operates on network topologies where each node observes a local quantity and can communicate with other nodes in an arbitrary point-to-point fashion. The main difference between Newscast EM and the standard EM algorithm is that the M-step in our case is implemented in a decentralized manner: (random) pairs of nodes repeatedly exchange their local parameter estimates and combine them by (weighted) averaging. We provide theoretical evidence and demonstrate experimentally that, under this protocol, nodes converge exponentially fast to the correct estimates in each M-step of the EM algorithm.
Finding sparse solutions to problems with convex constraints via concave programming

In this work, we consider a class of nonlinear optimization problems with convex constraints with the aim of computing sparse solutions. This is an important task arising in various fields such as machine learning, signal processing, data analysis. We adopt a concave optimization-based approach, we define an effective version of the Frank-Wolfe algorithm, and we prove the global convergence of the method. Finally, we report numerical results on test problems showing both the effectiveness of the concave approach and the efficiency of the implemented algorithm.
From Online Browsing to Offline Purchases: Analyzing Contextual Information in the Retail Business

Accurate recommender systems can enhance consumers' shop- ping experiences. In retail and many other business environments, extra contextual factors are usually available for building even more accurate recommender systems. The inuence of some factors is controversial in the industry. For instance, consumers' recent online exposure to products can decrease the chance of in-store purchase as consumers may choose to purchase products online. On the other hand, online exposure can be seen as an evidence of consumers' preference on products, which implies a higher chance of in-store purchase. The understanding of true inuence is important for product recommendation in-store in this case. The question is how to evaluate the relevance and the inuence of potential factors for prediction. Existing literature focuses on applying machine learning techniques to identify relevant contextual factors. While these methods are proven to be effective in some experiments, an alternative approach that can provide easy-to-interpret analysis on relevance and inuence is preferred in many situations. The paper introduces a computationally inexpensive approach to conduct preliminary relevance and inuence analysis for contextual information in retail business. Statistical tech- niques from medical research field are applied to analyze re- lationship between consumers' online exposure to retailer's e-commerce website, i.e., a contextual factor, and their of- ine in-store purchase decisions, i.e., the outcome to be predicted, based on a retail dataset provided by a large UK retail business with both online and offline presence. Unlike machine learning approaches, this analysis can be done even before a recommender system is built by using the proposed approach. This research further shows that the inuence of this contextual factor depends on extraneous attributes, such as consumers' ages and gender. This papers serves as a preliminary step to analyze relevant contextual factors for building context-aware recommender systems.
A Concept for Logic Self Repair

Predictions for the properties of integrated circuits and systems fabricated in emerging nano- technologies indicate a rising level of static and dynamic faults due to new fault mechanisms. Not only transient faults due to particle radiation are becoming a problem, but also wear-out effects on transistors and interconnects. While transient faults can be covered by well-known technologies such as error-correcting codes and triple modular redundancy, permanent faults essentially need a technology that provides built-in self repair (BISR). BISR is actually known and available for regular structures such as memory blocks, but is much more difficult to implement on irregular logic. The paper proposes a scheme for logic BISR, gives estimates for the associated overhead, and describes inherent limitations.
From the Cradle to the Grave: The Role of Macrophages in Erythropoiesis and Erythrophagocytosis

Erythropoiesis is a highly regulated process where sequential events ensure the proper differentiation of hematopoietic stem cells into, ultimately, red blood cells (RBCs). Macrophages in the bone marrow play an important role in hematopoiesis by providing signals that induce differentiation and proliferation of the earliest committed erythroid progenitors. Subsequent differentiation toward the erythroblast stage is accompanied by the formation of so-called erythroblastic islands where a central macrophage provides further cues to induce erythroblast differentiation, expansion, and hemoglobinization. Finally, erythroblasts extrude their nuclei that are phagocytosed by macrophages whereas the reticulocytes are released into the circulation. While in circulation, RBCs slowly accumulate damage that is repaired by macrophages of the spleen. Finally, after 120 days of circulation, senescent RBCs are removed from the circulation by splenic and liver macrophages. Macrophages are thus important for RBCs throughout their lifespan. Finally, in a range of diseases, the delicate interplay between macrophages and both developing and mature RBCs is disturbed. Here, we review the current knowledge on the contribution of macrophages to erythropoiesis and erythrophagocytosis in health and disease.
WaveCluster: a wavelet-based clustering approach for spatial data in very large databases

WaveCluster: a wavelet-based clustering approach for spatial data in very large databases Wavelets have found their way into numerous fields far removed from traditional signal analysis. WaveCluster was a new method for clustering large, d-dimensional datasets by decomposing the regions into grids and performing a wavelet transformation. The approximation from the transformation was used to effectively cluster and label items using known techniques. WaveCluster directly addressed some of the thorny issues associated with the growth of large spatial datasets by automating data mining in an efficient manner. A number of methods for partitioning datasets were discussed, but a grid based formulation was chosen for its ability to be processed quickly. Only a single sweep of the data was needed to quantize the regions using various measures. The only issue with the grid system was how to automatically determine the scale and size of each cell. If the cells were too small then unnecessary clusters were created. If the cells were too large, then many clusters were joined together. A heuristic was developed to iteratively find an acceptably sized cell, but this had a high overhead and they did not define the interpretation of acceptable. In the end, they settled the matter by noting that domain specific knowledge was critical. Still, the grid method had significant advantages over k-means clustering (which required pre-knowledge of the number of clusters), hierarchical clusters (which were order sensitive) and density based algorithms (which was very slow). The key in recognizing the usefulness of wavelets was seeing that the features of each cell could be transformed into a signal. Consequently, the feature space would have low frequency where there was clustering. By applying a low pass wavelet filter, this information could be retrieved. Using wavelets added other benefits, such as automatic unsupervised clustering, removal of noise and random data (by discarding the detail signals created from the decomposition) and the capability to use a multi-resolution process to iteratively find coarser clusters. A standard discrete wavelet transform was performed in their algorithm and by using the approximation signal, clusters emerged in their visualizations. To automate their discovery and labeling they needed to merely to find the connected components using a previously described algorithm. Then the original cells were labeled with their cluster, which was done through a lookup table (since the approximation data no longer had the original information). A point that was neglected was how this …
Perfil Ecuatoriano de las empresas metalmecánicas

El presente estudio refleja un analisis del desarrollo del mercado metalmecanico en el Ecuador, desde sus inicios hasta la actualidad, abarcando las oportunidades tanto nacionales como internacionales que tiene para expandirse. Porcentajes de crecimiento y montos de inversion que ha realizado esta division son senalados, adicionalmente de las cifras de empleos directos e indirectos que brinda. Se revisan los sectores y sub-clasificaciones de los mismos en los cuales se basa la produccion. Finalmente, se concluye con importantes reflexiones sobre el futuro de la industria que a pesar de ralentizacion, se augura crecimientos importantes para el avance productivo del pais.
Distortion analysis of bootstrap switch using volterra series

Linear behaviour of bootstrap switches is of critical importance in low-voltage analogue circuits and understanding the major factors affecting the linearity helps design a better switch. This study presents a theoretical approach for evaluating the distortion of bootstrap switches in the frequency domain based on the Volterra series. Five major factors affecting the linearity of the bootstrap switch are examined. In order to obtain a general design guideline the analysis is done in two parts. First, the distortion because of the non-linear I-V characteristic of the main transistor of the switch is considered. In the second part, the distortion because of sampling errors, such as clock feed-through and charge injection, are added to the analysis. The theoretical results are verified by circuit simulations in a 0.18 mum CMOS process, using HSpice.
Improvement of outdoor localization based on particle filter through video information's variable uncertainty

Localization of a mobile robot is a very important issue for robot's navigation. However, localization method with conventional wheel odometry has limits in case the wheel faces slippery conditions. As an alternative way, visual odometry has been researched continuously. However, this method alone has also difficulty for robust localization because wrong depth measurement can frequently occur and the error is accumulated continuously. Even though localization can be improved by using particle filter, this method is dependent on the accuracy of the reference map. For improving these drawbacks, this research utilized variable uncertainty useful for denoting accuracy of motion model from video information. Consequently, localization in the environments represented by inaccurate maps was improved compared to the conventional method.
PENGARUH PERCEIVED ORGANIZATIONAL OF SUPPORT, LEADER-MEMBER EXCHANGE, DAN STRES KERJA TERHADAP TURNOVER INTENTION KARYAWAN GENERASI Y DENGAN EMPLOYEE ENGAGEMENT SEBAGAI VARIABEL INTERVENING (Studi Kasus Pada Karyawan PT BPR Restu Artha Makmur)

Penelitian ini bertujuan: (1) Untuk menganalisis pengaruh perceived organizational of support, leader-member exchange, dan stres kerja terhadap e mployee engagement dan turnover intention ; (2) Untuk Menganalisis pengaruh perceived organizational of support, leader-member exchange, dan stres kerja terhadap Turnover Intention dengan dimediasi oleh e mployee engagement. Penelitian ini merupakan penelitian eksplanatori dengan metode pengambilan sampel secara sensus terhadap 60 karyawan generasi Y di PT BPR Restu Artha Makmur Kota Semarang. Teknik pengumpulan data menggunakan kuesioner yang menggunakan skala likert 5 poin. Teknik analisis yang digunakan adalah regresi linear berganda. Hasil penelitian menunjukkan bahwa: (1) perceived organizational of support berpengaruh positif-signifikan terhadap employee engagement dan negatif-signifikan terhadap turnover intention; (2) leader-member exchange berpengaruh positif-signifikan terhadap e mployee engagement dan negatif-signifikan terhadap turnover intention ; (3) stres kerja berpengaruh negatif-signifikan terhadap employee engagement dan positif-signifikan terhadap turnover intention; (4) employee engagement berpengaruh negatif-signifikan terhadap turnover intention; (5) employee engagement efektif dalam memediasi variabel perceived organizational of support, leader-member exchange, dan stres kerja terhadap turnover intention (R = 0, 71; Sign = 0.00). This study aims: (1) To analyze the effect of perceived organizational of support, leader-member exchange, and job stress on employee engagement and turnover intention; (2) To analyze the influence of perceived organizational of support, leader-member exchange, and work stress on Turnover Intention with mediating employee engagement. This research is explanatory research with census sampling method to 60 Y generation employees at PT BPR Restu Artha Makmur Semarang City. Technique of collecting data using questionnaires using Likert scale 5 points. The analysis technique used is multiple linear regression. The results showed that: (1) perceived organizational of support positively-significant to employee engagement and negative-significant to turnover intention; (2) leader-member exchange has a significant positive effect on employee engagement and significant negatives to turnover intention; (3) Job Stress has significant effect on employee engagement and positive-significant to turnover intention; (4) employee engagement has a significant negative effect on turnover intention; (5) effective employee engagement in mediating perceived organizational of support, leader-member exchange, and work stress on turnover intention (R = 0.71; Sign = 0.00).
Acclimation to Singlet Oxygen Stress in Chlamydomonas reinhardtii

ABSTRACT In an aerobic environment, responding to oxidative cues is critical for physiological adaptation (acclimation) to changing environmental conditions. The unicellular alga Chlamydomonas reinhardtii was tested for the ability to acclimate to specific forms of oxidative stress. Acclimation was defined as the ability of a sublethal pretreatment with a reactive oxygen species to activate defense responses that subsequently enhance survival of that stress. C. reinhardtii exhibited a strong acclimation response to rose bengal, a photosensitizing dye that produces singlet oxygen. This acclimation was dependent upon photosensitization and occurred only when pretreatment was administered in the light. Shifting cells from low light to high light also enhanced resistance to singlet oxygen, suggesting an overlap in high-light and singlet oxygen response pathways. Microarray analysis of RNA levels indicated that a relatively small number of genes respond to sublethal levels of singlet oxygen. Constitutive overexpression of either of two such genes, a glutathione peroxidase gene and a glutathione S-transferase gene, was sufficient to enhance singlet oxygen resistance. Escherichia coli and Saccharomyces cerevisiae exhibit well-defined responses to reactive oxygen but did not acclimate to singlet oxygen, possibly reflecting the relative importance of singlet oxygen stress for photosynthetic organisms.
Impact of Affect Heuristic, Fear and Anger on the Decision Making of Individual Investor: A Conceptual Study

Financial theories support the efficient market hypothesis, which assumes that prices are fair in the market and investors behave rationally while taking any investment decision. Individual Investors of the stock market are therefore thought to take rational decisions while making judgments and investment decisions. However, a lot of studies on behavioral finance have criticized the phenomenon of market efficiency and investor's rationality. The empirical evidences of these studies conclude the involvement of behavioral biases and psychological impacts on investor's judgments and decision making. Keeping this in mind the present study has focused on studying the impact of affect heuristic, fear and anger on individual investor's judgments and decision making. Overall discussion concludes the presence of behavioral biases in decision making process of investors.
Cash breeds success: The role of financing constraints in patent races

This paper studies the impact of financing constraints on the equilibrium of a patent race. We develop a model where firms finance their R&D expenditures with an investor who cannot verify their effort. We solve for the optimal financial contract of any firm along its best-response function. In equilibrium, any firm in the race is more likely to win the more cash and assets it holds prior to the race, and the less cash and assets its rivals hold prior to the race. We use NBER evidence from pharmaceutical patents awarded between 1975 and 1999 in the US, patent citations, and COMPUSTAT to measure the effect of all the racing firms' cash holdings on the equilibrium winning probabilities. The empirical findings support our theoretical predictions.
Exploring the dynamics of the biocybernetic loop in physiological computing

Physiological computing is a highly multidisciplinary emerging field in which the spread of results across several application areas and disciplines creates a challenge of combining the lessons learned from various studies. The thesis comprises diverse publications that together create a privileged position for contributing to a common understanding of the roles and uses of physiological computing systems, generalizability of results across application areas, the theoretical grounding of the field (as with the various ways the psychophysiological states of the user can be modeled), and the emerging data analysis approaches from the domain of machine learning. The core of physiological computing systems has been built around the concept of biocybernetic loop, aimed at providing real-time adaptation to the cognitions, motivations, and emotions of the user. However, the traditional concept of the biocybernetic loop has been both self-regulatory and immediate; that is, the system adapts to the user immediately. The thesis presents an argument that this is too narrow a view of physiological computing, and it explores scenarios wherein the physiological signals are used not only to adapt to the user but to aid system developers in designing better systems, as well as to aid other users of the system. The thesis includes eight case studies designed to answer three research questions: 1) what are the various dynamics the biocybernetic loop can
Wearable computing for patients with coronary diseases: Gathering efforts by comparing methods

Cardiovascular diseases are a prime cause of mortality and morbidity around the world. The World Health Organization names this as a global epidemic identifying it as a big challenge to Information and Communication Technologies that can provide valuable tools to improve population health and well-being. In tandem with a strategy to provide information and education to individuals at risk, several projects across the world at national or regional levels are trying to address this challenge. The HEARTRONIC project developed an innovative system for prevention and early warning by continuous monitoring the heart conditions. This system is wearable by the patient, monitors and analyzes the ECG, and in the event of results that could predict a heart attack or stroke an alert message is sent to a server and then relayed to the responsible healthcare professional. The system uses ECG processing for automatic detection of abnormal functioning. First response actions are taken but the healthcare professionals are always in the control. The BIOMED-TEL project developed an innovative remote patient monitor that supervises 24 hours/7 days the main patient's vital signals in its environment. These signs are: SpO2, ECG one derivation, arterial blood pressure (BP), in conjunction with the body vibration acquired from chest zone and, glucose concentration in blood all above mentioned signs being relevant for the health patient status. With the correlation of the signals, the remote monitor is able to dynamical adapt his working regime from local storage of data acquired (as a classical holter) to continuously transmission of data acquired from patient to the hospital server, providing a quick time intervention of the health care professional in case of patient's alarm or emergency situation. Both projects are gathering efforts by comparing methods in order to assess the best practices and address the technical challenges that came across the development of such useful platforms.