Miracle-dz/UniFAR-FTUs huggingface dataset:
Ability of γδ T cells to modulate the Foxp3 T cell response is dependent on adenosine

Whether γδ T cells inhibit or enhance the Foxp3 T cell response depends upon their activation status. The critical enhancing effector in the supernatant is adenosine. Activated γδ T cells express adenosine receptors at high levels, which enables them to deprive Foxp3+ T cells of adenosine, and to inhibit their expansion. Meanwhile, cell-free supernatants of γδ T cell cultures enhance Foxp3 T cell expansion. Thus, inhibition and enhancement by γδ T cells of Foxp3 T cell response are a reflection of the balance between adenosine production and absorption by γδ T cells. Non-activated γδ T cells produce adenosine but bind little, and thus enhance the Foxp3 T cell response. Activated γδ T cells express high density of adenosine receptors and have a greatly increased ability to bind adenosine. Extracellular adenosine metabolism and expression of adenosine receptor A2ARs by γδ T cells played a major role in the outcome of γδ and Foxp3 T cell interactions. A better understanding of the functional conversion of γδ T cells could lead to γδ T cell-targeted immunotherapies for related diseases.
Crystal Structure of a Soluble Cleaved HIV-1 Envelope Trimer

Knowing the Enemy Infection of host cells by HIV-1 is mediated by an envelope glycoprotein (Env) trimeric spike on the surface of the virus. Proteins comprising the Env trimer must be cleaved for infectivity, and thus viral fusion involves three Env conformations. The flexibility of the Env trimer has made it a challenge to determine a high-resolution structure, although such a structure is key both for understanding trimer function and for guiding vaccine design. Lyumkis et al. (p. 1484) and Julien et al. (p. 1477) studied soluble cleaved trimers stabilized by specific mutations but that have kept a near-native antigenicity profile. Lyumkis et al. present a high-resolution structure of the trimer in complex with a broadly neutralizing antibody, and Julien et al. present a crystal structure of the trimer in complex with another broadly neutralizing antibody. Key structural features dictate how the HIV envelope protein functions and interacts with the human immune system. HIV-1 entry into CD4+ target cells is mediated by cleaved envelope glycoprotein (Env) trimers that have been challenging to characterize structurally. Here, we describe the crystal structure at 4.7 angstroms of a soluble, cleaved Env trimer that is stabilized and antigenically near-native (termed the BG505 SOSIP.664 gp140 trimer) in complex with a potent broadly neutralizing antibody, PGT122. The structure shows a prefusion state of gp41, the interaction between the component gp120 and gp41 subunits, and how a close association between the gp120 V1/V2/V3 loops stabilizes the trimer apex around the threefold axis. The complete epitope of PGT122 on the trimer involves gp120 V1, V3, and several surrounding glycans. This trimer structure advances our understanding of how Env functions and is presented to the immune system, and provides a blueprint for structure-based vaccine design.
Dynamic pricing with limited supply

We consider the problem of designing revenue maximizing online posted-price mechanisms when the seller has limited supply. A seller has k identical items for sale and is facing n potential buyers ("agents") that are arriving sequentially. Each agent is interested in buying one item. Each agent's value for an item is an independent sample from some fixed (but unknown) distribution with support [0,1]. The seller offers a take-it-or-leave-it price to each arriving agent (possibly different for different agents), and aims to maximize his expected revenue. We focus on mechanisms that do not use any information about the distribution; such mechanisms are called "detail-free" (an alternative term is "prior-independent"). They are desirable because knowing the distribution is unrealistic in many practical scenarios. We study how the revenue of such mechanisms compares to the revenue of the optimal offline mechanism that knows the distribution ("offline benchmark"). We present a detail-free online posted-price mechanism whose revenue is at most O((k log n)2/3) less than the offline benchmark, for every distribution that is regular. In fact, this guarantee holds without any assumptions if the benchmark is relaxed to fixed-price mechanisms. Further, we prove a matching lower bound. The performance guarantee for the same mechanism can be improved to O(k log n), with a distribution-dependent constant, if the ratio k/n is sufficiently small. We show that, in the worst case over all demand distributions, this is essentially the best rate that can be obtained with a distribution-specific constant.
The Hybrid CramÉr–Rao Bound on Broadside DOA Estimation of Extended Sources in Presence of Array Errors

In this correspondence we derive explicit expressions for the hybrid Cramer-Rao lower bound (HCRB) on the estimation accuracy of signal direction of arrival (DOA) from data collected by randomly perturbed arrays. The presence of a wavefront spatial decorrelation, which is modeled as a multiplicative correlated noise, has also been taken into account in the data model, since it is typical in those applications involving extended sources. In particular, we consider perturbations in sensor positions. Existing approaches to DOA HCRB calculation do not consider the presence of multiplicative noise and are referred to the assumption of small perturbations only, still not being worked out explicitly. Here, we assume that the impinging wavefronts are coming from broadside or more generally from a narrow DOA sector, allowing the explicit derivation of the HCRB for any variance of the sensor positioning errors in the line-of-sight direction. This scenario corresponds to the typical operative condition of remote sensing systems such as synthetic aperture radar (SAR) multibaseline interferometers, for which a few HCRB sample curves are reported.
Coordinated forward error recovery for composite Web services

This paper proposes a solution based on forward error recovery, oriented towards providing dependability of composite Web services. While exploiting their possible support for fault tolerance (e.g., transactional support at the level of each service), the proposed solution has no impact on the autonomy of the individual Web services, our solution lies in system structuring in terms of co-operative atomic actions that have a well-defined behavior, both in the absence and in the presence of service failures. More specifically, we define the notion of Web Service Composition Action (WSCA), based on the Coordinated Atomic Action concept, which allows structuring composite Web services in terms of dependable actions. Fault tolerance can then be obtained as an emergent property of the aggregation of several potentially non-dependable services. We further introduce a framework enabling the development of composite Web services based on WSCAs, consisting of an XML-based language for the specification of WSCAs.
The optimal routes for the vessels to transport empty containers under different shipping service networks design

In any manufacturing industry, one of the areas where business leadership can focus to achieve cost reduction is inventory management. Inventory ties up working capital which could be better employed elsewhere. The main problem in inventory management is to determine inventory levels and order raw materials and produce finished products accordingly. The goal of this paper is to present a simple framework developed to assist end-users in their decision making process for inventory control. The framework is based on time series oriented forecasting methods to select the reordering strategies for independent demand of a product for small manufacturing companies.
Temporal updating scheme for probabilistic neural network with application to satellite cloud classification

In cloud classification from satellite imagery, temporal change in the images is one of the main factors that causes degradation in the classifier performance. In this paper, a novel temporal updating approach is developed for probabilistic neural network (PNN) classifiers that can be used to track temporal changes in a sequence of images. This is done by utilizing the temporal contextual information and adjusting the PNN to adapt to such changes. Whenever a new set of images arrives, an initial classification is first performed using the PNN updated up to the last frame while at the same time, a prediction using Markov chain models is also made based on the classification results of the previous frame. The results of both the old PNN and the predictor are then compared. Depending on the outcome, either a supervised or an unsupervised updating scheme is used to update the PNN classifier. Maximum likelihood (ML) criterion is adopted in both the training and updating schemes. The proposed scheme is examined on both a simulated data set and the Geostationary Operational Environmental Satellite (GOES) 8 satellite cloud imagery data. These results indicate the improvements in the classification accuracy when the proposed scheme is used.
Practical Timing and Frequency Synchronization for OFDM-Based Cooperative Systems

In this paper, we investigate the timing and carrier frequency offset (CFO) synchronization problem in decode and forward cooperative systems operating over frequency selective channels. A training sequence which consists of one orthogonal frequency-division multiplexing (OFDM) block having a tile structure in the frequency domain is proposed to perform synchronization. Timing offsets are estimated using correlation-type algorithms. By inserting some null subcarriers in the proposed tile structure, we propose a computationally efficient subspace decomposition-based algorithm for CFO estimation. The issue of optimal tile length is studied both theoretically and through simulations. By judiciously designing the tile size of the pilot, the proposed algorithms are shown to have better performance, in terms of synchronization errors and bit error rate, than the time-division multiplexing-based training method and the computationally demanding space-alternating generalized expectation-maximization algorithm.
A Model Predictive Power Control Approach for a Three-Phase Single-Stage Grid-Tied PV Module-Integrated Converter

This paper presents the concept of three-phase module-integrated converters (MICs) incorporated in grid-tied large-scale photovoltaic (PV) systems. The current-source converter with dc voltage boost capability, namely the single-stage power conversion system, is proposed for the three-phase PV MIC system. A model predictive scheme with low switching frequency is designed to control the proposed topology in such a way that provides a certain amount of active and reactive power in steady-state operation and also provides a proper ratio of reactive power under transient conditions to meet the low-voltage ride through regulations. To predict the future behavior of current control values and switching states, a discrete-time model of the MIC is developed in the synchronous reference frame. It is demonstrated that the injected active and reactive power can be controlled by minimizing the cost function introduced in the predictive switching algorithm. The proposed structure is simulated in MATLAB/SIMULINK software. An experimental verification is provided to justify the performance of the proposed control method through a 300-VA laboratory prototype. The results verify the desired performance of the proposed control scheme for exchanging both active and reactive powers between the PV MIC and the grid within different operating conditions.
Identification of a novel synaptic protein, TMTC3, involved in periventricular nodular heterotopia with intellectual disability and epilepsy

Abstract Defects in neuronal migration cause brain malformations, which are associated with intellectual disability (ID) and epilepsy. Using exome sequencing, we identified compound heterozygous variants (p.Arg71His and p. Leu729ThrfsTer6) in TMTC3, encoding transmembrane and tetratricopeptide repeat containing 3, in four siblings with nocturnal seizures and ID. Three of the four siblings have periventricular nodular heterotopia (PVNH), a common brain malformation caused by failure of neurons to migrate from the ventricular zone to the cortex. Expression analysis using patient-derived cells confirmed reduced TMTC3 transcript levels and loss of the TMTC3 protein compared to parental and control cells. As TMTC3 function is currently unexplored in the brain, we gathered support for a neurobiological role for TMTC3 by generating flies with post-mitotic neuron-specific knockdown of the highly conserved Drosophila melanogaster TMTC3 ortholog, CG4050/tmtc3. Neuron-specific knockdown of tmtc3 in flies resulted in increased susceptibility to induced seizures. Importantly, this phenotype was rescued by neuron-specific expression of human TMTC3, suggesting a role for TMTC3 in seizure biology. In addition, we observed co-localization of TMTC3 in the rat brain with vesicular GABA transporter (VGAT), a presynaptic marker for inhibitory synapses. TMTC3 is localized at VGAT positive pre-synaptic terminals and boutons in the rat hypothalamus and piriform cortex, suggesting a role for TMTC3 in the regulation of GABAergic inhibitory synapses. TMTC3 did not co-localize with Vglut2, a presynaptic marker for excitatory neurons. Our data identified TMTC3 as a synaptic protein that is involved in PVNH with ID and epilepsy, in addition to its previously described association with cobblestone lissencephaly.
Riboswitching with ciprofloxacin—development and characterization of a novel RNA regulator

Abstract RNA molecules play important and diverse regulatory roles in the cell. Inspired by this natural versatility, RNA devices are increasingly important for many synthetic biology applications, e.g. optimizing engineered metabolic pathways, gene therapeutics or building up complex logical units. A major advantage of RNA is the possibility of de novo design of RNA-based sensing domains via an in vitro selection process (SELEX). Here, we describe development of a novel ciprofloxacin-responsive riboswitch by in vitro selection and next-generation sequencing-guided cellular screening. The riboswitch recognizes the small molecule drug ciprofloxacin with a KD in the low nanomolar range and adopts a pseudoknot fold stabilized by ligand binding. It efficiently interferes with gene expression both in lower and higher eukaryotes. By controlling an auxotrophy marker and a resistance gene, respectively, we demonstrate efficient, scalable and programmable control of cellular survival in yeast. The applied strategy for the development of the ciprofloxacin riboswitch is easily transferrable to any small molecule target of choice and will thus broaden the spectrum of RNA regulators considerably.
Audio keywords generation for sports video analysis

Sports video has attracted a global viewership. Research effort in this area has been focused on semantic event detection in sports video to facilitate accessing and browsing. Most of the event detection methods in sports video are based on visual features. However, being a significant component of sports video, audio may also play an important role in semantic event detection. In this paper, we have borrowed the concept of the “keyword” from the text mining domain to define a set of specific audio sounds. These specific audio sounds refer to a set of game-specific sounds with strong relationships to the actions of players, referees, commentators, and audience, which are the reference points for interesting sports events. Unlike low-level features, audio keywords can be considered as a mid-level representation, able to facilitate high-level analysis from the semantic concept point of view. Audio keywords are created from low-level audio features with learning by support vector machines. With the help of video shots, the created audio keywords can be used to detect semantic events in sports video by Hidden Markov Model (HMM) learning. Experiments on creating audio keywords and, subsequently, event detection based on audio keywords have been very encouraging. Based on the experimental results, we believe that the audio keyword is an effective representation that is able to achieve satisfying results for event detection in sports video. Application in three sports types demonstrates the practicality of the proposed method.
Coalgebras and their logics

Some comments about the last Logic Column, on nominal logic. Pierre Lescanne points out that the terminology "de Bruijn levels" was introduced in the paper Explicit Substitutions with de Bruijn's Levels, by Pierre Lescanne and Jocelyne Rouyer-Degli, presented at the 1995 RTA conference. He also points out that Stoy diagrams were probably invented by Stoy, but appear in work by Bourbaki as early as 1939 (published in 1954). Merci, Pierre.That article also initiated what is bound to be an interesting discussion. The critique of higherorder abstract syntax in that article prompted Karl Crary and Robert Harper to prepare a response to the leveled criticisms. The response should appear in an upcoming Column.In this issue, Alexander Kurz describes recent work on the topic of specifying properties of transition systems. It turns out that by giving a suitably abstract description of transition systems as coalgebras, we can derive logics for capturing properties of these transition systems in a rather elegant way.
Nearest common ancestors: a survey and a new distributed algorithm

Several papers describe linear time algorithms to preprocess a tree, such that one can answer subsequent nearest common ancestor queries in constant time. Here, we survey these algorithms and related results. A common idea used by all the algorithms for the problem is that a solution for complete binary trees is straightforward. Furthermore, for complete binary trees we can easily solve the problem in a distributed way by labeling the nodes of the tree such that from the labels of two nodes alone one can compute the label of their nearest common ancestor. Whether it is possible to distribute the data structure into short labels associated with the nodes is important for several applications such as routing. Therefore, related labeling problems have received a lot of attention recently.Previous optimal algorithms for nearest common ancestor queries work using some mapping from a general tree to a complete binary tree. However, it is not clear how to distribute the data structures obtained using these mappings. We conclude our survey with a new simple algorithm that labels the nodes of a rooted tree such that from the labels of two nodes alone one can compute in constant time the label of their nearest common ancestor. The labels assigned by our algorithm are of size $O(\log n)$ bits where $n$ is the number of nodes in the tree. The algorithm runs in $O(n)$ time.
Syllable-Pattern-Based Unknown-Morpheme Segmentation and Estimation for Hybrid Part-of-Speech Tagging of Korean

Most errors in Korean morphological analysis and part-of-speech (POS) tagging are caused by unknown morphemes. This paper presents a syllable-pattern-based generalized unknown-morpheme-estimation method with POSTAG (POStech TAGger),1 which is a statistical and rule-based hybrid POS tagging system. This method of guessing unknown morphemes is based on a combination of a morpheme pattern dictionary that encodes general lexical patterns of Korean morphemes with a posteriori syllable trigram estimation. The syllable trigrams help to calculate lexical probabilities of the unknown morphemes and are utilized to search for the best tagging result. This method can guess the POS tags of unknown morphemes regardless of their numbers and/or positions in an eojeol (a Korean spacing unit similar to an English word), which is not possible with other systems for tagging Korean. In a series of experiments using three different domain corpora, the system achieved a 97 tagging accuracy even though 10 of the morphemes in the test corpora were unknown. It also achieved very high coverage and accuracy of estimation for all classes of unknown morphemes. The binary code of POSTAG is open to the public for research and evaluation purposes at http://nlp.postech. ac.kr/. Follow the link OpenResourcesDownLoad.
iPDA: integrated protein disorder analyzer

This article presents a web server iPDA, which aims at identifying the disordered regions of a query protein. Automatic prediction of disordered regions from protein sequences is an important problem in the study of structural biology. The proposed classifier DisPSSMP2 is different from several existing disorder predictors by its employment of position-specific scoring matrices with respect to physicochemical properties (PSSMP), where the physicochemical properties adopted here especially take the disorder propensity of amino acids into account. The web server iPDA integrates DisPSSMP2 with several other sequence predictors in order to investigate the functional role of the detected disordered region. The predicted information includes sequence conservation, secondary structure, sequence complexity and hydrophobic clusters. According to the proportion of the secondary structure elements predicted, iPDA dynamically adjusts the cutting threshold of determining protein disorder. Furthermore, a pattern mining package for detecting sequence conservation is embedded in iPDA for discovering potential binding regions of the query protein, which is really helpful to uncovering the relationship between protein function and its primary sequence. The web service is available at http://biominer.bime. ntu.edu. tw/ipda and mirrored at http://biominer.cse. yzu.edu. tw/ipda.
Down-regulation of the IbEXP1 gene enhanced storage root development in sweetpotato

The role of an expansin gene (IbEXP1) in the formation of the storage root (SR) was investigated by expression pattern analysis and characterization of IbEXP1-antisense sweetpotato (Ipomoea batatas cv. Yulmi) plants in an attempt to elucidate the molecular mechanism underlying SR development in sweetpotato. The transcript level of IbEXP1 was high in the fibrous root (FR) and petiole at the FR stage, but decreased significantly at the young storage root (YSR) stage. IbEXP1-antisense plants cultured in vitro produced FRs which were both thicker and shorter than those of wild-type (WT) plants. Elongation growth of the epidermal cells was significantly reduced, and metaxylem and cambium cell proliferation was markedly enhanced in the FRs of IbEXP1-antisense plants, resulting in an earlier thickening growth in these plants relative to WT plants. There was a marked reduction in the lignification of the central stele of the FRs of the IbEXP1-antisense plants, suggesting that the FRs of the mutant plants possessed a higher potential than those of WT plants to develop into SRs. IbEXP1-antisense plants cultured in soil produced a larger number of SRs and, consequently, total SR weight per IbEXP1-antisense plant was greater than that per WT plant. These results demonstrate that SR development was accelerated in IbEXP1-antisense plants and suggest that IbEXP1 plays a negative role in the formation of SR by suppressing the proliferation of metaxylem and cambium cells to inhibit the initial thickening growth of SRs. IbEXP1 is the first sweetpotato gene whose role in SR development has been directly identified in soil-grown transgenic sweetpotato plants.