Miracle-dz/UniFAR-FTUs huggingface dataset:
ICOS Costimulation Requires IL-2 and Can Be Prevented by CTLA-4 Engagement1

We investigated the relationship between ICOS, CD28, CTLA-4, and IL-2 to gain a better understanding of this family of costimulatory receptors in the immune response. Using magnetic beads coated with anti-CD3 and varying amounts of anti-ICOS and anti-CTLA-4 Abs, we show that CTLA-4 ligation blocks ICOS costimulation. In addition to inhibiting cellular proliferation, CTLA-4 engagement prevented ICOS-costimulated T cells from producing IL-4, IL-10, and IL-13. Both an indirect and direct mechanism of CTLA-4’s actions were examined. First, CTLA-4 engagement on resting cells was found to indirectly block ICOS costimulation by interferring with the signals needed to induce ICOS cell surface expression. Second, on preactivated cells that had high levels of ICOS expression, CTLA-4 ligation blocked the ICOS-mediated induction of IL-4, IL-10, and IL-13, suggesting an interference with downstream signaling pathways. The addition of IL-2 not only overcame both mechanisms, but also greatly augmented the level of cellular activation suggesting synergy between ICOS and IL-2 signaling. This cooperation between ICOS and IL-2 signaling was explored further by showing that the minimum level of IL-2 produced by ICOS costimulation was required for T cell proliferation. Finally, exogenous IL-2 was required for sustained growth of ICOS-costimulated T cells. These results indicate that stringent control of ICOS costimulation is maintained initially by CTLA-4 engagement and later by a requirement for exogenous IL-2.
Distilling Word Embeddings: An Encoding Approach

Distilling knowledge from a well-trained cumbersome network to a small one has recently become a new research topic, as lightweight neural networks with high performance are particularly in need in various resource-restricted systems. This paper addresses the problem of distilling word embeddings for NLP tasks. We propose an encoding approach to distill task-specific knowledge from a set of high-dimensional embeddings, so that we can reduce model complexity by a large margin as well as retain high accuracy, achieving a good compromise between efficiency and performance. Experiments reveal the phenomenon that distilling knowledge from cumbersome embeddings is better than directly training neural networks with small embeddings.
Incremental  $N$ -Mode SVD for Large-Scale Multilinear Generative Models

Tensor decomposition is frequently used in image processing and machine learning for its ability to express higher order characteristics of data. Among tensor decomposition methods, N-mode singular value decomposition (SVD) is widely used owing to its simplicity. However, the data dimension often becomes too large to perform N-mode SVD directly due to memory limitation. An incremental method to N-mode SVD can be used to resolve this issue, but existing approaches only provide a result, which is just enough to solve discriminative problems, not the full factorization result. In this paper, we present a complete derivation of the incremental N-mode SVD, which can be applied to generative models, accompanied by a technique that can reduce the computational cost by reordering calculations. The proposed incremental N-mode SVD can also be used effectively to update the current result of N-mode SVD when new training data is received. The proposed method provides a very good approximation of N-mode SVD for the experimental data, and requires much less computation in updating a multilinear model.
An efficient energy hole alleviating algorithm for wireless sensor networks

Many consumer products in the home environment are managed by the Wireless Sensor Networks (WSNs). However, the energy hole problem in the WSNs which with logical ring topology and uniformly distributed sensors is usually caused by the energy exhaustion of the sensors which distributed in the first radius range of the sink. This paper firstly analyzed the energy consumption model of the sensor, the data transmission model of the sensor, and the energy consumption distribution model of the WSNs. Then, a WSN Energy Hole Alleviating (WSNEHA) algorithm, which is based on the data forwarding and router selection strategy, is proposed. The WSNEHPA adopts the data forwarding and routing selection strategy to balance the energy consumption of the sensors in the first radius range of the sink. Experimental results demonstrate that WSNEHPA can efficiently balance the energy consumption of the sensors in the first radius range of the sink, and that the lifetime of the WSNs can be extended efficiently.
IRREDUCIBILITY CRITERIA FOR SUMS OF TWO RELATIVELY PRIME POLYNOMIALS

We provide irreducibility conditions for polynomials of the form f(X) + pkg(X), with f and g relatively prime polynomials with integer coefficients, deg f < deg g, p a prime number and k a positive integer. In particular, we prove that if k is prime to deg g - deg f and pk exceeds a certain bound depending on the coefficients of f and g, then f(X) + pkg(X) is irreducible over ℚ.
A Non-linear GPU Thread Map for Triangular Domains

There is a stage in the GPU computing pipeline where a grid of thread-blocks, in \textit{parallel space}, is mapped onto the problem domain, in \textit{data space}. Since the parallel space is restricted to a box type geometry, the mapping approach is typically a $k$-dimensional bounding box (BB) that covers a $p$-dimensional data space. Threads that fall inside the domain perform computations while threads that fall outside are discarded at runtime. In this work we study the case of mapping threads efficiently onto triangular domain problems and propose a block-space linear map $\lambda(\omega)$, based on the properties of the lower triangular matrix, that reduces the number of unnnecessary threads from $\mathcal{O}(n^2)$ to $\mathcal{O}(n)$. Performance results for global memory accesses show an improvement of up to $18\%$ with respect to the \textit{bounding-box} approach, placing $\lambda(\omega)$ on second place below the \textit{rectangular-box} approach and above the \textit{recursive-partition} and \textit{upper-triangular} approaches. For shared memory scenarios $\lambda(\omega)$ was the fastest approach achieving $7\%$ of performance improvement while preserving thread locality. The results obtained in this work make $\lambda(\omega)$ an interesting map for efficient GPU computing on parallel problems that define a triangular domain with or without neighborhood interactions. The extension to tetrahedral domains is analyzed, with applications to triplet-interaction n-body applications.
Completeness and incompleteness for intuitionistic logic

Abstract We call a logic regular for a semantics when the satisfaction predicate for at least one of its nontheorems is closed under double negation. Such intuitionistic theories as second-order Heyting arithmetic HAS and the intuitionistic set theory IZF prove completeness for no regular logics, no matter how simple or complicated. Any extensions of those theories proving completeness for regular logics are classical, i.e., they derive the tertium non datur. When an intuitionistic metatheory features anticlassical principles or recognizes that a logic regular for a semantics is nonclassical, it proves explicitly that the logic is incomplete with respect to that semantics. Logics regular relative to Tarski, Beth and Kripke semantics form a large collection that includes propositional and predicate intuitionistic, intermediate and classical logics. These results are corollaries of a single theorem. A variant of its proof yields a generalization of the Gödel-Kreisel Theorem linking weak completeness for intuitionistic predicate logic to Markov's Principle.
On burstiness-aware search for document sequences

As the number and size of large timestamped collections (e.g. sequences of digitized newspapers, periodicals, blogs) increase, the problem of efficiently indexing and searching such data becomes more important. Term burstiness has been extensively researched as a mechanism to address event detection in the context of such collections. In this paper, we explore how burstiness information can be further utilized to enhance the search process. We present a novel approach to model the burstiness of a term, using discrepancy theory concepts. This allows us to build a parameter-free, linear-time approach to identify the time intervals of maximum burstiness for a given term. Finally, we describe the first burstiness-driven search framework and thoroughly evaluate our approach in the context of different scenarios.
Airtime Fairness for IEEE 802.11 Multirate Networks

Under a multirate network scenario, the IEEE 802.11 DCF MAC fails to provide airtime fairness for all competing stations since the protocol is designed for ensuring max-min throughput fairness. As such, the maximum achievable throughput by any station gets bounded by the slowest transmitting peer. In this paper, we present an analytical model to study the delay and throughput characteristics of such networks so that the rate anomaly problem of IEEE DCF multirate networks could be mitigated. We call our proposal time fair CSMA (TFCSMA) which utilizes an interesting baseline property for estimating a target throughput for each competing station so that its minimum contention window could be adjusted in a distributed manner. As opposed to the previous work in this area, TFCSMA is ideally suited for practical scenarios where stations frequently adapt their data rates to changing channel conditions. In addition, TFCSMA also accounts for packet errors due to the time varying properties of the wireless channel. We thoroughly compare the performance of our proposed protocol with IEEE 802.11 and other existing protocols under different network scenarios and traffic conditions. Our comprehensive simulations validate the efficacy of our method toward providing high throughput and time fair channel allocation.
Tomato NAC Transcription Factor SlSRN1 Positively Regulates Defense Response against Biotic Stress but Negatively Regulates Abiotic Stress Response

Biotic and abiotic stresses are major unfavorable factors that affect crop productivity worldwide. NAC proteins comprise a large family of transcription factors that play important roles in plant growth and development as well as in responses to biotic and abiotic stresses. In a virus-induced gene silencing-based screening to identify genes that are involved in defense response against Botrytis cinerea, we identified a tomato NAC gene SlSRN1 (Solanum lycopersicum Stress-related NAC1). SlSRN1 is a plasma membrane-localized protein with transactivation activity in yeast. Expression of SlSRN1 was significantly induced by infection with B. cinerea or Pseudomonas syringae pv. tomato (Pst) DC3000, leading to 6–8 folds higher than that in the mock-inoculated plants. Expression of SlSRN1 was also induced by salicylic acid, jasmonic acid and 1-amino cyclopropane-1-carboxylic acid and by drought stress. Silencing of SlSRN1 resulted in increased severity of diseases caused by B. cinerea and Pst DC3000. However, silencing of SlSRN1 resulted in increased tolerance against oxidative and drought stresses. Furthermore, silencing of SlSRN1 accelerated accumulation of reactive oxygen species but attenuated expression of defense genes after infection by B. cinerea. Our results demonstrate that SlSRN1 is a positive regulator of defense response against B. cinerea and Pst DC3000 but is a negative regulator for oxidative and drought stress response in tomato.
Lidocaine Cyclodextrin complex Ophthalmic Drop, a New Topical Anesthetic Choice

Background Topical anesthesia is a safe and cost-effective method considered as the first-choice in many procedures. Due to the physiological characteristics of eye, most of the local anesthetics cannot efficiently penetrate through the conjunctiva deep to tenon. The aim of this pilot study was to find a new form of lidocaine to give a sufficient level of anesthesia. Methods: Lidocaine Cyclodextrin complex ophthalmic drop was produced and its pharmacological properties were studied [tested] in standard temperature and pressure. 30 patients (18 males, 12 females) with the mean age of 30.68±8.02 years enrolled in this clinical trial. All the patients were fully informed and signed the ethics committee consent forms. The patients were given tetracaine drop as the anesthetic: 3 drops separated 2 minute apart 10 min before the intervention. If we achieved a sufficient level of anesthesia, the procedure was done after. If the patient could not tolerate the procedure, the method was changed to lidocaine drop (administered after wash-out period like the first drop). The last option was conventional injection method if the patient could not tolerate the procedure with the second method either.We used this type of anesthesia for conventional procedures such as forced duction test, symblepharon, pterygium, and disport injection into extra-ocular muscles. All the procedures were done by one surgeon in a university hospital. We used a 0 to 10 visual analogue scale for pain and two 0 to 4 patient and physician satisfaction scales designed for this study. Results The mean pain score was 7.53±0.90 in group 1 and 3.03±1.83 in group 2 (P=0.00). Patient and surgeon satisfaction in group 1 were 1.33±0.48 and 1.40±0.56 respectively; while 3.23±1.00 and 3.56±0.77 for group 2 (P=0.00). Tetracaine drop could not induce sufficient anesthesia for none of the patients. Cyclodextrin based lidocaine drop was successful except For two patients for whom we changed the anesthesia to Sub-conjunctival injection method. Conclusion Our newly manufactured cyclodextrin based lidocaine eye drop could successfully induce sufficient anesthesia for 28 of 30 patients. Further studies with larger sample sizes are now being designed to find more clinical evidence about this method.
Diversity of Evoked Astrocyte Ca2+ Dynamics Quantified through Experimental Measurements and Mathematical Modeling

Astrocytes are a major cell type in the mammalian brain. They are not electrically excitable, but generate prominent Ca2+ signals related to a wide variety of critical functions. The mechanisms driving these Ca2+ events remain incompletely understood. In this study, we integrate Ca2+ imaging, quantitative data analysis, and mechanistic computational modeling to study the spatial and temporal heterogeneity of cortical astrocyte Ca2+ transients evoked by focal application of ATP in mouse brain slices. Based on experimental results, we tune a single-compartment mathematical model of IP3-dependent Ca2+ responses in astrocytes and use that model to study response heterogeneity. Using information from the experimental data and the underlying bifurcation structure of our mathematical model, we categorize all astrocyte Ca2+ responses into four general types based on their temporal characteristics: Single-Peak, Multi-Peak, Plateau, and Long-Lasting responses. We find that the distribution of experimentally-recorded response types depends on the location within an astrocyte, with somatic responses dominated by Single-Peak (SP) responses and large and small processes generating more Multi-Peak responses. On the other hand, response kinetics differ more between cells and trials than with location within a given astrocyte. We use the computational model to elucidate possible sources of Ca2+ response variability: (1) temporal dynamics of IP3, and (2) relative flux rates through Ca2+ channels and pumps. Our model also predicts the effects of blocking Ca2+ channels/pumps; for example, blocking store-operated Ca2+ (SOC) channels in the model eliminates Plateau and Long-Lasting responses (consistent with previous experimental observations). Finally, we propose that observed differences in response type distributions between astrocyte somas and processes can be attributed to systematic differences in IP3 rise durations and Ca2+ flux rates.
Predictors of Life Satisfaction in Stroke Survivors and Spousal Caregivers After Inpatient Rehabilitation

&NA; A global measure of life satisfaction has become increasingly important as an adjunctive outcome of healthcare interventions for people with disabilities, including those caused by stroke. Life satisfaction of stroke survivors may affect caregiving spouses, as well. The purpose of this study was to identify, among many physical and psychosocial variables, specific variables that were associated with life satisfaction at 12 months after discharge from inpatient rehabilitation, and variables that were predictive of life satisfaction 1 year later (at 24 months). Between 12 and 24 months, life satisfaction decreased for stroke survivors, while it increased for caregiving spouses. The relationship between the couple (mutuality) was the only variable that was a significant predictor of life satisfaction for both stroke survivors and their spouses.
The Differences among Eyes-Closed, Eyes-Open and Attention States: An EEG Study

Electroencephalographic (EEG) activity was recorded in normal adults during a three sessions' paradigm, including eyes-closed (EC), eyes-open (EO) resting condition with binocular fixation on a center cross, and a visual attention task. In attention task, subjects were required to keep binocular fixation on a center cross, focus on right or left visual field per block, and respond to the infrequent targets at the attended visual field. Mean theta (4-7 Hz) and beta (14-30 Hz) powers over 128 channels were weaker in the EO than in the EC and attention task, respectively. Mean alpha (8-13 Hz) power was stronger in the EC than in the EO and attention task. Comparisons of theta, alpha and beta rhythms powers between EC, EO and attention task were calculated by the standardized low resolution brain electromagnetic tomography (sLORETA). The results revealed that alpha rhythms in frontal, parietal, and occipital areas were stronger in power in EC than in EO and attention task, but no significant differences in theta and beta rhythms. Furthermore, normalized powers showed that distributive alpha rhythms powers decreased gradually from EC, EO to attention task. The present results suggest that alpha rhythms power and its allocation index human different brain states.
Life Cycle Environmental Impacts of Electricity from Biogas Produced by Anaerobic Digestion

The aim of this study was to evaluate life cycle environmental impacts associated with the generation of electricity from biogas produced by the anaerobic digestion (AD) of agricultural products and waste. Five real plants in Italy were considered, using maize silage, slurry, and tomato waste as feedstocks and cogenerating electricity and heat; the latter is not utilized. The results suggest that maize silage and the operation of anaerobic digesters, including open storage of digestate, are the main contributors to the impacts of biogas electricity. The system that uses animal slurry is the best option, except for the marine and terrestrial ecotoxicity. The results also suggest that it is environmentally better to have smaller plants using slurry and waste rather than bigger installations, which require maize silage to operate efficiently. Electricity from biogas is environmentally more sustainable than grid electricity for seven out of 11 impacts considered. However, in comparison with natural gas, biogas electricity is worse for seven out of 11 impacts. It also has mostly higher impacts than other renewables, with a few exceptions, notably solar photovoltaics. Thus, for the AD systems and mesophilic operating conditions considered in this study, biogas electricity can help reduce greenhouse gas (GHG) emissions relative to a fossil-intensive electricity mix; however, some other impacts increase. If mitigation of climate change is the main aim, other renewables have a greater potential to reduce GHG emissions. If, in addition to this, other impacts are considered, then hydro, wind, and geothermal power are better alternatives to biogas electricity. However, utilization of heat would improve significantly its environmental sustainability, particularly global warming potential, summer smog, and the depletion of abiotic resources and the ozone layer. Further improvements can be achieved by banning open digestate storage to prevent methane emissions and regulating digestate spreading onto land to minimize emissions of ammonia and related environmental impacts.
Teaching at Its Best: A Research-Based Resource for College Instructors

Excerpt: If you are new to the scholarship of teaching and learning and want to get a solid foundation on how to make your courses more effective learning experiences, this book is an excellent choice. Teaching at Its Best is aimed directly at faculty to use for themselves, rather than for faculty developers or administrators. The content is a combination of “how to. ” suggestions that will improve general teaching effectiveness as well as “what is. ” sections that discuss different learning theories and methods. Active-learning
Expression of Human Paraoxonase 1 Decreases Superoxide Levels and Alters Bacterial Colonization in the Gut of Drosophila melanogaster

Paraoxonases (PON) are a family of proteins (PON1, 2 and 3) with multiple enzymatic activities. PON1 interferes with homoserine lactone-mediated quorum sensing in bacteria and with reactive oxygen species (ROS) in humans and mice. PON1 gene mutations have been linked to multiple traits, including aging, and diseases of the cardiovascular, nervous and gastrointestinal system. The overlapping enzymatic activities in the PON family members and high linkage disequilibrium rates within their polymorphisms confound animal and human studies of PON1 function. In contrast, arthropods such as Drosophila melanogaster have no PON homologs, resulting in an ideal model to study interactions between PON genotype and host phenotypes. We hypothesized that expression of PON1 in D. melanogaster would alter ROS. We found that PON1 alters expression of multiple oxidative stress genes and decreases superoxide anion levels in normal and germ-free D. melanogaster. We also found differences in the composition of the gut microbiota, with a remarkable increase in levels of Lactobacillus plantarum and associated changes in expression of antimicrobial and cuticle-related genes. PON1 expression directly decreased superoxide anion levels and altered bacterial colonization of the gut and its gene expression profile, highlighting the complex nature of the interaction between host genotype and gut microbiota. We speculate that the interaction between some genotypes and human diseases may be mediated by the presence of certain gut bacteria that can induce specific immune responses in the gut and other host tissues.
The Heart of Counseling

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