Miracle-dz/UniFAR-FTUs huggingface dataset:
Natural killer cells activity in a metastatic colorectal cancer patient with complete and long lasting response to therapy

Here we report a case of a 70-year-old man who received adjuvant chemotherapy with fluorouracile, folinic acid and oxaliplatin after a left hemicolectomy for a stage IIIb adenocarcinoma in May 2009. During follow-up he de-veloped abdominal lymphnodes metastases evidenced by positron emission tomography- computed tomography (PET-CT) scan and increase of carcinoembryonic antigen (CEA) level. Chemotherapy with capecitabine, oxaliplatin and bevacizumab was started in April 2012. Restaging showed a complete response and normalization of CEA. The patient received maintenance therapy with bevacizumab which was stopped in December 2013 for patient choice. In October 2014, a new increase in CEA was documented and PET-CT scan showed lung metastases. Analysis of RAS status revealed the absence of mutations, then the patient started a second-line chemotherapy with fluorouracile, folinic acid, irinotecan (folfiri) and panitumumab achieving, in January 2015, a complete response and normalization of CEA. Thereafter, folfiri was discontinued for toxicity; furthermore, upon the third occurrence of a grade 3 dermatologic toxicity, panitumumab was continued from June 2015 at 60% of the original dose and it was administered every three weeks. Until presentation of this case, the patient maintains a complete response, has no symptoms of disease and CEA is normal. Interestingly, this patient presented a high proportion of circulating natural killer (NK) cells (35.1%) with high cytotoxic activity against tumor cells. Study on the role of NK in patients with advanced colorectal cancer are ongoing.
Effect of 7‐nitroindazole on body temperature and methamphetamine‐induced dopamine toxicity

THE present study was undertaken to examine the role of temperature on the ability of 7-nitroindazole (7-NI) to prevent methamphetamine-induced dopamine (DA) neurotoxicity. Male Swiss-Webster mice received methamphetamine alone or in combination with 7-NI at either room temperature (20 ± 1°C) or at 28 ± 1°C. At 20°C, 7-NI produced hypothermic effects and afforded total protection against methamphetamine-induced DA depletions in the striatum. At 28 ± 1°C, 7-NI produced minimal effects on body temperature and failed to prevent methamphetamine-induced DA reductions. These findings indicate that the neuroprotection afforded by 7-NI is likely related to its ability to produce hypothermia because agents that produce hypothermia and/or prevent hyperthermia are known to attenuate methamphetamine-induced neurotoxicity.
Downsizing in America: Reality, Causes, and Consequences

Noting that corporate downsizing in the U.S. deserves more attention—even the ASQ has yet to publish an article on it— the authors of this book propose to offer the “most comprehensive treatment” (p. 5) of the issue to date. They begin by focusing on downsizing trends using various sources, including their data on 133 downsizings between 1993 and 1997. The sources generally link the business cycle to job cuts, which have tended to decrease during economic upturns (the mid-to-later 1980s and the mid-1990s) and to increase during downturns (the early 1990s, the later 1990s, and the early 2000s). Among the 133 firms studied, there is evidence that large (manufacturing) firms have tended to downsize, while smaller (non-manufacturing) ones actually have tended to upsize. There also is evidence that personnel reducers during 1993–1997 have been below the national average on three indicators involving the effects of reductions: change in profits, stock values, and output from 1990 to 1998.
Identification of Small-Molecule Modulators of Mouse SVZ Progenitor Cell Proliferation and Differentiation Through High-Throughput Screening

Adult mouse subventricular zone (SVZ) neural stem/progenitor cells are multipotent self-renewing cells that retain the capacity to generate the major cell types of the central nervous system in vitro and in vivo. The relative ease of expanding SVZ cells in culture as neurospheres makes them an ideal model for carrying out large-scale screening to identify compounds that regulate neural progenitor cell proliferation and differentiation. The authors have developed an adenosine triphosphate—based cell proliferation assay using adult SVZ cells to identify small molecules that activate or inhibit progenitor cell proliferation. This assay was miniaturized to a 1536-well format for high-throughput screening (HTS) of >1 million small-molecule compounds, and 325 and 581 compounds were confirmed as potential inducers of SVZ cell proliferation and differentiation, respectively. A number of these compounds were identified as having a selective proliferative and differentiation effect on SVZ cells versus mouse Neuro2a neuroblastoma cells. These compounds can potentially be useful pharmacological tools to modulate resident stem cells and neurogenesis in the adult brain. This study represents a novel application of primary somatic stem cells in the HTS of a large-scale compound library. (Journal of Biomolecular Screening 2009:319-329)
Similarity Comparisons for Interactive Fine-Grained Categorization

Current human-in-the-loop fine-grained visual categorization systems depend on a predefined vocabulary of attributes and parts, usually determined by experts. In this work, we move away from that expert-driven and attribute-centric paradigm and present a novel interactive classification system that incorporates computer vision and perceptual similarity metrics in a unified framework. At test time, users are asked to judge relative similarity between a query image and various sets of images, these general queries do not require expert-defined terminology and are applicable to other domains and basic-level categories, enabling a flexible, efficient, and scalable system for fine-grained categorization with humans in the loop. Our system outperforms existing state-of-the-art systems for relevance feedback-based image retrieval as well as interactive classification, resulting in a reduction of up to 43% in the average number of questions needed to correctly classify an image.
Development and use of the Geriatric Anxiety Inventory (GAI)

Anxiety symptoms and anxiety disorders are highly prevalent among older people. A widely accepted brief instrument to measure dimensional anxiety in both healthy older adults and those with mental health problems seen in a variety of settings has been lacking. A 20-item scale (the Geraitric Anxiety Inventory, or GAI) was devised, with a simple response format and straightforward scoring. The instrument demonstrated good reliability in both normal community and psychiatric samples (Cronbach’s alpha 0.91 and 0.93, respectively). Concurrent validity with other measures was high; inter-rater and test-retest reliability were excellent. The ability of the GAI to discriminate between patients with and without any anxiety disorder [F(1,44)=16.87, p=0.0002] was also excellent. Receiver operating characteristic (ROC) analysis indicated an optimum cut point of 8/9 to identify older patients with any anxiety disorder, correctly classifying 78 per cent of patients (sensitivity 73 per cent, specificity 80 per cent). The GAI has been translated into several languages and is in use in six countries, in both clinical and neurological populations, and with evidence of good pre-post utility in treatment studies. We conclude that the GAI is a promising new instrument for use in geriatric clinical populations.
Minimum Weight Perfect Matching via Blossom Belief Propagation

Max-product Belief Propagation (BP) is a popular message-passing algorithm for computing a Maximum-A-Posteriori (MAP) assignment over a distribution represented by a Graphical Model (GM). It has been shown that BP can solve a number of combinatorial optimization problems including minimum weight matching, shortest path, network flow and vertex cover under the following common assumption: the respective Linear Programming (LP) relaxation is tight, i.e., no integrality gap is present. However, when LP shows an integrality gap, no model has been known which can be solved systematically via sequential applications of BP. In this paper, we develop the first such algorithm, coined Blossom-BP, for solving the minimum weight matching problem over arbitrary graphs. Each step of the sequential algorithm requires applying BP over a modified graph constructed by contractions and expansions of blossoms, i.e., odd sets of vertices. Our scheme guarantees termination in O(n2) of BP runs, where n is the number of vertices in the original graph. In essence, the Blossom-BP offers a distributed version of the celebrated Edmonds' Blossom algorithm by jumping at once over many sub-steps with a single BP. Moreover, our result provides an interpretation of the Edmonds' algorithm as a sequence of LPs.
Development of emotion-cognition relations

Studies of the development of emotion-cognition relations, C. Izard talking with feeling - integrating affective and linguistic experssions in early language development, L. Bloom & R. Beckwith young children's theory of mind and emotion, P.L. Harris, C.N. Johnson, et al cognitive-emotional interactions in the brain, J.E. LeDoux infant's expectations in play - the joy of peek-a-boo, W.G. Parrot, H. Gleitman the causal organisation of emotional knowledge - a developmental study, N.L. Stein, L.J. Levine understanding the motivational role of affect - life-span research from an attributional perspective, B. Weiner, S. Graham.
Increased Expression of Tumor Necrosis Factor-Alpha in the Rat Hippocampus after Acute Homocysteine Administration

Background and Purpose: This paper evaluated the effect of acute homocysteine administration on inflammatory cytokine tumor necrosis factor-alpha (TNF-α) expression and neuronal apoptosis in the rat hippocampus and investigated the effects of vitamin C treatment on homocysteine-induced inflammation and neuronal death. Methods: Subjects were three-week-old, male Sprague-Dawley rats. Rats for the control group, we injected saline solution into the rats’ abdominal cavities for one week. Rats in the second group received 1 injection of homocysteine (11 mmol/kg) into their abdominal cavities after 1 week of saline solution administration. For the third group, we injected the rats with vitamin C (100 mg/kg) for a week, followed by 1 injection of homocysteine. The hippocampi were stained with an anti-TNF-α antibody, and apoptosis was evaluated using the TUNEL staining method. Results: The homocysteine-injected rats had strong TNF-α expression in every hippocampal region. Vitamin C significantly reduced TNF-α expression in the hippocampus’s CA1 region. Acute homocysteine administration did not cause apoptosis in the hippocampus. Conclusions: The pro-inflammatory cytokine TNF-α may mediate elevated homocysteine levels’ contributions to inflammatory reactions, and vitamin C has some protective effect on inflammatory reactions in the CA1 hippocampal region.
Human-Robot Interaction in Network Robot Systems

In this paper we study a novel approach in networked robotics for optimal allocation with interchangeable objective functions, from minimizing the worst-case cost of any agent in a multi-robot team in time-critical missions, to minimizing the team usage of resources. We propose a general model for flexible mission planning, using hierarchical task networks as descriptive framework, the multiple traveling salesmen as optimization model, and distributed simulated annealing for solution search in very large solution spaces. This proposal has the potential to find the theoretically optimal solution. We briefly comment on the feasibility and usefulness of full replication of data in critical missions. We present a working implementation in simulation and preliminary plans for urban environment experiments, and also an implementation using current market-based techniques for comparison against our proposal. For our simulations we use a coverage problem, where our algorithm enables us to determine the best starting point for the robots, exploiting the flexibility of HTNs.
Uncompressed video transmission in portable devices for wireless video mirroring service

Wireless transmission of uncompressed video guarantees higher quality with lower latency than compressed video transmission. Although current wireless technologies cannot fully cover required data rates of about a few Gb/s for full high definition resolution, some wireless technologies such as ultra-wideband (UWB) provide 1 Gb/s data rate which is adequate for uncompressed video transmission in portable devices. In this paper, we propose an uncompressed video transmission system for wireless mirroring services in potable devices. We firstly simulated the performance of uncompressed video transmission using 1 Gb/s UWB technology. Then we implemented hardware-based uncompressed video processing block and Gb/s wireless MAC accelerator. Finally, we show the possibilities of uncompressed video transmission using single 1 Gb/s UWB physical layer (PHY) and extended transmission for more higher resolution using multiple UWB PHYs.
Getting Started: An Introduction to Dynamic Psychotherapy

Getting Started provides answers to questions that confront all beginning therapists, such as How do I start? What do I say? What if the client challenges me? What if the client is silent? How do I deal with fees? What about confidentiality? How should I end the sessions? It also answers those fundamental general concerns, like: how does psychotherapy work? How can I be helpful to my patients? Many books claim to be simply written and easy for an inexperienced therapist to understand. This one really is. It is user friendly and written with a minimum of jargon. Dr. Joel Kotin gives numerous examples of common situations and problems that therapists regularly encounter and hen tells the reader how to approach them. Dr. Kotin's tone is reassuring and supportive throughout.
The quest for consciousness : a neurobiological approach

We may not be able to make you love reading, but the quest for consciousness a neurobiological approach will lead you to love reading starting from now. Book is the window to open the new world. The world that you want is in the better stage and level. World will always guide you to even the prestige stage of the life. You know, this is some of how reading will give you the kindness. In this case, more books you read more knowledge you know, but it can mean also the bore is full.
Proactive Caching of Music Videos based on Audio Features, Mood, and Genre

The preferred channel for listening to music is shifting towards the Internet and especially to mobile networks. Here, the overall traffic is predicted to grow by 45% annually till 2021. However, the resulting increase in network traffic challenges mobile operators. As a result, methods are researched to decrease costly transit traffic and the traffic load inside operator networks using in-network and client-side caching. Additionally to traditional reactive caching, recent works show that proactive caching increases cache efficiency. Thus, in this work, a mobile network using proactive caching is assumed. As music represents the most popular content category on YouTube, this work focuses on studying the potential of proactively caching content of this particular category using a YouTube trace containing over 4 million music video user sessions. The contribution of this work is threefold: First, music content-specific user behavior is derived and audio features of the content are analyzed. Second, using these audio features, genre and mood classifiers are compared in order to guide the design of new proactive caching policies. Third, a novel trace-based evaluation methodology for music-specific proactive in-network caching is proposed and used to evaluate novel proactive caching policies to serve either an aggregate of users or individual clients.
A Review of Enhanced Cluster Based Routing Protocol for Mobile Nodes in Wireless Sensor Network

The current emerging technology is Mobile Wireless sensor Network (MWSNs) which consist of hundreds of tiny, inexpensive, resource constrained sensor nodes. The major challenging task that the wireless sensor suffer from is Routing and the critical issue while designing the Wireless sensor Network is Energy Saving. There are many routing protocols that have been developed and among them is clustering based. In clustering based routing protocol the network is partitioned into small clusters and each cluster is examined and controlled by a single node called Cluster Head (CH). In this paper, we review an enhanced algorithm for Low Energy Adaptive Clustering HierarchyMobile(LEACH-M) protocol called ECBR-MWSN which is Enhanced Cluster Based Routing Protocol for Mobile Nodes in Wireless Sensor Network. ECBR protocol selects the Cluster Head (CH) using the parameters of highest residual energy, lowest mobility and least distance from Base Station which aimed to prolonging the lifetime of the sensor networks by balancing the energy consumption of the nodes. Then compare the performance of our proposed algorithm with the cluster based protocols using ns2 simulator. The simulation result indicates that the proposed algorithm gives better performance in terms of higher packet delivery ratio, throughput, energy consumption, routing overhead, and delay.
Kinetic Analysis of Enterococcus faecium l,d-Transpeptidase Inactivation by Carbapenems

ABSTRACT Bypass of classical penicillin-binding proteins by the l,d-transpeptidase of Enterococcus faecium (Ldtfm) leads to high-level ampicillin resistance in E. faecium mutants, whereas carbapenems remain the lone highly active β-lactams. Kinetics of Ldtfm inactivation was determined for four commercial carbapenems and a derivative obtained by introducing a minimal ethyl group at position 2. We show that the bulky side chains of commercial carbapenems have both positive and negative effects in preventing hydrolysis of the acyl enzyme and impairing drug binding.
Image synthesis using adjoint photons

The most straightforward image synthesis algorithm is to follow photon-like particles from luminaires through the environment. These particles scatter or are absorbed when they interact with a surface or a volume. They contribute to the image if and when they strike a sensor. Such an algorithm implicitly solves the light transport equation. Alternatively. adjoint photons can be traced from the sensor to the luminaires to produce the same image. This "adjoint photon" tracing algorithm is described, and its strengths and weaknesses are discussed, as well as details needed to make adjoint photon tracing practical.
N-Best List Reranking using Higher Level Phonetic, Lexical, Syntactic and Semantic Knowledge Sources

This paper presents a novel methodology to improve large vocabulary continuous speech recognizer (LVCSR) hypotheses using additional phonetic, lexical, syntactic and semantic knowledge. Such additional higher level knowledge sources are unavailable during the LVCSR decoding due to the various constraints placed on the successful deployment of such information sources. This paper focuses on the extraction of WER improvements from the LVCSR n-best list using the additional higher level knowledge sources as the nucleus of a reranking mechanism. We illustrate the improvements obtained for the conversational speech transcription task and also for the directed dialog speech utterance transcription task in a grammar tuning application
From MAP to Marginals: Variational Inference in Bayesian Submodular Models

Submodular optimization has found many applications in machine learning and beyond. We carry out the first systematic investigation of inference in probabilistic models defined through submodular functions, generalizing regular pairwise MRFs and Determinantal Point Processes. In particular, we present L-FIELD, a variational approach to general log-submodular and log-supermodular distributions based on sub- and supergradients. We obtain both lower and upper bounds on the log-partition function, which enables us to compute probability intervals for marginals, conditionals and marginal likelihoods. We also obtain fully factorized approximate posteriors, at the same computational cost as ordinary submodular optimization. Our framework results in convex problems for optimizing over differentials of submodular functions, which we show how to optimally solve. We provide theoretical guarantees of the approximation quality with respect to the curvature of the function. We further establish natural relations between our variational approach and the classical mean-field method. Lastly, we empirically demonstrate the accuracy of our inference scheme on several submodular models.
Using the Ferret as an Animal Model for Investigating Influenza Antiviral Effectiveness

The concern of the emergence of a pandemic influenza virus has sparked an increased effort toward the development and testing of novel influenza antivirals. Central to this is the animal model of influenza infection, which has played an important role in understanding treatment effectiveness and the effect of antivirals on host immune responses. Among the different animal models of influenza, ferrets can be considered the most suitable for antiviral studies as they display most of the human-like symptoms following influenza infections, they can be infected with human influenza virus without prior viral adaptation and have the ability to transmit influenza virus efficiently between one another. However, an accurate assessment of the effectiveness of an antiviral treatment in ferrets is dependent on three major experimental considerations encompassing firstly, the volume and titer of virus, and the route of viral inoculation. Secondly, the route and dose of drug administration, and lastly, the different methods used to assess clinical symptoms, viral shedding kinetics and host immune responses in the ferrets. A good understanding of these areas is necessary to achieve data that can accurately inform the human use of influenza antivirals. In this review, we discuss the current progress and the challenges faced in these three major areas when using the ferret model to measure influenza antiviral effectiveness.
Feature selection methods for text classification

We consider feature selection for text classification both theoretically and empirically. Our main result is an unsupervised feature selection strategy for which we give worst-case theoretical guarantees on the generalization power of the resultant classification function f with respect to the classification function f obtained when keeping all the features. To the best of our knowledge, this is the first feature selection method with such guarantees. In addition, the analysis leads to insights as to when and why this feature selection strategy will perform well in practice. We then use the TechTC-100, 20-Newsgroups, and Reuters-RCV2 data sets to evaluate empirically the performance of this and two simpler but related feature selection strategies against two commonly-used strategies. Our empirical evaluation shows that the strategy with provable performance guarantees performs well in comparison with other commonly-used feature selection strategies. In addition, it performs better on certain datasets under very aggressive feature selection.
Hoare-style reasoning with (algebraic) continuations

Continuations are programming abstractions that allow for manipulating the "future" of a computation. Amongst their many applications, they enable implementing unstructured program flow through higher-order control operators such as callcc. In this paper we develop a Hoare-style logic for the verification of programs with higher-order control, in the presence of dynamic state. This is done by designing a dependent type theory with first class callcc and abort operators, where pre- and postconditions of programs are tracked through types. Our operators are algebraic in the sense of Plotkin and Power, and Jaskelioff, to reduce the annotation burden and enable verification by symbolic evaluation. We illustrate working with the logic by verifying a number of characteristic examples.