Miracle-dz/UniFAR-FTUs huggingface dataset:
Distributed Learning with Regularized Least Squares

We study distributed learning with the least squares regularization scheme in a reproducing kernel Hilbert space (RKHS). By a divide-and-conquer approach, the algorithm partitions a data set into disjoint data subsets, applies the least squares regularization scheme to each data subset to produce an output function, and then takes an average of the individual output functions as a final global estimator or predictor. We show with error bounds in expectation in both the $L^2$-metric and RKHS-metric that the global output function of this distributed learning is a good approximation to the algorithm processing the whole data in one single machine. Our error bounds are sharp and stated in a general setting without any eigenfunction assumption. The analysis is achieved by a novel second order decomposition of operator differences in our integral operator approach. Even for the classical least squares regularization scheme in the RKHS associated with a general kernel, we give the best learning rate in the literature.
Analysis of Non-binary Hybrid LDPC Codes

This paper is eligible for the student paper award. In this paper, we analyse asymptotically a new class of LDPC codes called non-binary hybrid LDPC codes, which has been recently introduced in L. Sassatelli and D. Declerq [2006]. We use density evolution techniques to derive a stability condition for hybrid LDPC codes, and prove their threshold behavior. We study this stability condition to conclude on asymptotic advantages of hybrid LDPC codes compared to their non-hybrid counterparts.
Plant Breeding: A Success Story to be Continued Thanks to the Advances in Genomics

Conventional plant breeding mostly relies upon the generation of new genetic combinations by sexual hybridization and the subsequent application of selection methods on phenotypically evaluated individuals and populations. This approach has been extremely efficient in providing a continuous supply of improved cultivars that have resulted in a dramatic increase of yield in most major crops. These yield increases have allowed time after time beating neo-Malthusian predictions that food production could not keep the pace of population growth in the twentieth century and beyond (Fedoroff, 2010). According to FAO data, in less than 50 years (1961–2009) the world average of cereal yields has increased from 1.35 to 3.51 t/ha. Thanks to these yield improvements, the total production of cereals has raised from 877·106 to 2489·106 t with just an increase of 9% in this period in the acreage devoted to these staple crops. These unparalleled increases in yield have been possible thanks to improved cultivation techniques in combination with new cultivars. The new cultivars have been developed for adaptation to new management practices or growing conditions and vice versa, in a clear example to exploitation of genotype × environment (G × E) interaction. One of the most recalled examples of the success of this approach comes from the so-called Green Revolution (Jain, 2010). The identification of dwarf and semi-dwarf genes in rice and wheat made possible the development of non-lodging cultivars with high yield in response to fertilization (Hedden, 2003). The adoption of the new cultivars combined with higher levels of fertilization resulted in dramatic yield increases in Southeast Asia (rice) and Mexico (wheat). Another illustration of the achievements of breeding involves maize in the US, where yields have increased by more than five-fold since 1930. These impressive yield increases have been preceded by the adoption of breeding innovations which, sequentially consisted on the selection within open-pollinated varieties, development of double and three-way hybrids, simple F1 hybrids, and GMO F1 hybrids (Hallauer and Carena, 2009). These success stories in the three major crops have a parallel in many other crops of different botanical families and with different uses.
Convergence analysis and optimal scheduling for multiple concatenated codes

An interesting practical consideration for decoding of serial or parallel concatenated codes with more than two components is the determination of the lowest complexity component decoder schedule which results in convergence. This correspondence presents an algorithm that finds such an optimal decoder schedule. A technique is also given for combining and projecting a series of three-dimensional extrinsic information transfer (EXIT) functions onto a single two-dimensional EXIT chart. This is a useful technique for visualizing the convergence threshold for multiple concatenated codes and provides a design tool for concatenated codes with more than two components.
Extending an Indonesian Semantic Analysis-based Question Answering System with Linguistic and World Knowledge Axioms

We adopt a previously developed model of deep syntactic and semantic processing to support question answering for Bahasa Indonesia, and extend it by adding a number of axioms designed to encode useful knowledge for answering questions, thus increasing the inferential power of the QA system. We believe this approach can increase the robustness of semantic analysis-based QA systems, whilst simultaneously lightening the burden of complexity in designing semantic attachment rules that transduce logical forms from syntactic structures. We show how these added axioms enable the system to answer questions which previously could not have been answered.
High-Speed Industrial Vision Applications Using an Embedded Smart Sensor System

A compact, low-power line-sensor vision system has been developed for use in high-speed industrial machine vision applications. The system contains a 2times256 dual-line optical transient address-event sensor with autonomous, self-signaling pixels and pixel-level precision time-stamping, and an embedded DSP platform for real-time address-event processing. Initial pre-processing of the visual information at the pixel level results in a complete suppression of image data redundancy, resulting in drastically reduced processing power requirements at the embedded system level. The sensor system features sub-microsecond time resolution, outperforming traditional, frame-based linescan sensor systems by up to two orders of magnitude. The system features are beneficial for high-speed machine vision applications in the fields of industrial automation and automotive. In this paper, the system architecture and application results examples are presented.
High Speed Downlink Packet Access efficient turbo decoder architecture : 3 GPP Advanced Turbo Decoder

The multi-application specific instruction set processor (ASIP) architecture is a promising candidate for flexible high-throughput turbo decoders. This in brief proposes a network-on-chip (NoC) structure for multi-ASIP turbo decoders. The process of turbo decoding are studied and the addressing patterns for turbo codes in long term evolution (LTE) and High Speed Downlink Packet Access (HSDPA) is analyzed. Based on this analysis, the two techniques such as subnetworking and calculation sequence have been proposed for reducing the complexity of the NoC. The implementation result shows that the proposed structure provides an improvement of 53% for HSDPA and 133% for LTE in throughput/area efficiency compared with state-of-the-art NoC solutions. Multi-application specific instruction processor is combined with new decoding algorithm to increase the throughput.
Seasonality of the Transpiration Fraction and Its Controls Across Typical Ecosystems Within the Heihe River Basin

Understanding the seasonality of the transpiration fraction (T/ET) of total terrestrial evapotranspiration (ET) is vital for coupling ecological and hydrological systems and quantifying the heterogeneity among various ecosystems. In this study, a two‐source model was used to estimate T/ET in five ecosystems over the Heihe River Basin. In situ measurements of daily energy flux, sap flow, and surface soil temperature were compared with model outputs for 2014 and 2015. Agreement between model predictions and observations demonstrates good performance in capturing the ecosystem seasonality of T/ET. In addition, sensitivity analysis indicated that the model is insensitive to errors in measured input variables and parameters. T/ET among the five sites showed only slight interannual fluctuations while exhibited significant seasonality. All the ecosystems presented a single‐peak trend, reaching the maximum value in July and fluctuating day to day. During the growing season, average T/ET was the highest for the cropland ecosystem (0.80 ± 0.13), followed by the alpine meadow ecosystem (0.79 ± 0.12), the desert riparian forest Populus euphratica (0.67 ± 0.07), the Tamarix ramosissima Ledeb desert riparian shrub ecosystem (0.67 ± 0.06), and the alpine swamp meadow (0.55 ± 0.23). Leaf area index exerted a first‐order control on T/ET and showed divergence among the five ecosystems because of different vegetation dynamics and environmental conditions (e.g., water availability or vapor pressure deficits). This study quantified transpiration fraction across diverse ecosystems within the same water basin and emphasized the biotic controls on the seasonality of the transpiration fraction.
Small Molecule Radiopharmaceuticals – A Review of Current Approaches

Radiopharmaceuticals are an integral component of nuclear medicine and are widely applied in diagnostics and therapy. Though widely applied, the development of an “ideal” radiopharmaceutical can be challenging. Issues such as specificity, selectivity, sensitivity, and feasible chemistry challenge the design and synthesis of radiopharmaceuticals. Over time, strategies to address the issues have evolved by making use of new technological advances in the fields of biology and chemistry. This review presents the application of few advances in design and synthesis of radiopharmaceuticals. The topics covered are bivalent ligand approach and lipidization as part of design modifications for enhanced selectivity and sensitivity and novel synthetic strategies for optimized chemistry and radiolabeling of radiopharmaceuticals.
Reactive Hyperemia in Arterioles and Capillaries of Frog Skeletal Muscle following Microocclusion

We studied the localization of blood flow control in skeletal muscle by short-term microocclusions (30–60 seconds) of capillaries and arterioles of the pectoralis muscle in anesthetized frogs (Rana pipiens). The muscle was surgically exposed to permit transillumination and measurement of red cell velocity in the microvessels, but innervation and blood supply were kept intact. About one-third of the arterioles showed postocclusion hyperemia. In some muscles every arteriole showed hyperemia following occlusion, but in others none responded, presumably because of preparatory trauma. The average duration of hyperemia after a 1-minute occlusion was 74 ± 45 (SD) seconds. We also compared the effectiveness of arteriolar and capillary occlusions in producing reactive hyperemia in capillaries. Peak capillary blood flow after occlusion of the supply arteriole was 233% above control, and flow debt repayment was 278%. After occlusion of several capillaries, peak capillary blood flow was 67% above control, and flow debt repayment was 74%. In an individual capillary, peak blood flow after occlusion of that capillary was 15% above control, and flow debt repayment was 13%. In a majority of instances there was no discernible reactive hyperemia with single capillary occlusion. The results do not support the concept that flow in individual capillaries is regulated in accordance with each capillary's metabolic environment. Rather, flow in a capillary appears to depend on the metabolic environment of the arteriole supplying that capillary.
Building a Reactive Immune System for Software Services

We propose a reactive approach for handling a wide variety of software failures, ranging from remotely exploitable vulnerabilities to more mundane bugs that cause abnormal program termination (e.g., illegal memory dereference) or other recognizable bad behavior (e.g., computational denial of service). Our emphasis is in creating "self-healing" software that can protect itself against a recurring fault until a more comprehensive fix is applied. Briefly, our system monitors an application during its execution using a variety of external software probes, trying to localize (in terms of code regions) observed faults. In future runs of the application, the "faulty" region of code will be executed by an instruction-level emulator. The emulator will check for recurrences of previously seen faults before each instruction is executed. When a fault is detected, we recover program execution to a safe control flow. Using the emulator for small pieces of code, as directed by the observed failure, allows us to minimize the performance impact on the immunized application. We discuss the overall system architecture and a prototype implementation for the x86 platform. We show the effectiveness of our approach against a range of attacks and other software failures in real applications such as Apache, sshd, and Bind. Our preliminary performance evaluation shows that although full emulation can be prohibitively expensive, selective emulation can incur as little as 30% performance overhead relative to an uninstrumented (but failure-prone) instance of Apache. Although this overhead is significant, we believe our work is a promising first step in developing self-healing software.
Water Use and Drought Responses of Cool-Season Turfgrasses

Evapotranspiration (ET) rates of four turf grass species were compared in Rhode Island to aid in the selection of grasses with lower water requirements. ET was measured under well-watered conditions using weighing lysimeters placed into field plots of mature turf. Measurements were obtained regularly from July to September in 1984 and 1985. Average daily ET ranged from 0.23 to 0.41 cm of water/day for: Paa pratensis L. cvs. 'Baron' and 'Enmundi', Lolium perenne L. cv. 'Yorktown II', Festuca rubra var. commutata Gaud. cv. 'Jamestown', and Festuca ovina var. duriuscula L. Koch cv. 'Tournament'. Significant differences in ET rates were found between species. Kentucky bluegrass and perennial ryegrass transpired more than the fescues. Potential ET was computed using the modified Penman equation and the pan evaporation methods. Crop coefficients (KCs) were calculated to determine the predictive consistency of the methods. Seasonal KCs based on the Penman equation ranged from 0.88 to 1.09. KCs based on pan evaporation showed more variability, ranging from 0.86 to 1.35.
A Meta-learning Method for Concept Drift

The knowledge hidden in evolving data may change with time, this issue is known as concept drift. It often causes a learning system to decrease its prediction accuracy. Most existing techniques apply ensemble methods to improve learning performance on concept drift. In this paper, we propose a novel meta learning approach for this issue and develop a method: Multi-Step Learning (MSL). In our method, a MSL learner is structured in a recursive manner, which contains all the base learners maintained in a hierarchy, ensuring the learned concepts are traceable. We evaluated MSL and two ensemble techniques on three synthetic datasets, which contain a number of drastic concept drifts. The experimental results show that the proposed method generally performs better than the ensemble techniques in terms of prediction accuracy.
Shape conditions and phonological context

This paper builds on Zwicky's (1986) notion of shape condition, that is, a rule that specifies the phonological shape of inflected forms "by reference to triggers at least some of which lie outside the syntactic word". Zwicky observes that "many rules traditionally classified as external sandhi rules are [shape conditions]". They are not phonological rules in the usual sense, since they only apply to specific lexical items and are active within syntactic rather than phonological domains. Shape conditions are problematic in many standard grammar architectures. On the one hand, they seem to be constraints on lexical entries, while on the other hand, they make reference to the syntactic context. Hayes (1990) has sketched a theory of "precompiled phrasal phonology" in which allomorph choice is conditioned by subcategorization frames in lexical entries. However, his approach is not formalized in any detail, and moreover makes the implicit claim that the relation between a shape condition target and its triggers can be equated with the syntactic relation between a lexical head and its complement. Although this assumption holds good for the Hausa phenomena he addresses, we do not believe that it holds in general. HPSG appears to offer promising framework for formalizing something like Hayes' approach, but the standard machinery also makes it hard to distinguish a shape condition trigger from a complement. In order to overcome this difficulty, we develop the notion of phonological context: a feature of signs which allows us to condition allomorphic alternation in terms of (i) the phonological edges, and (ii) the syntactic properties of an expression's immediate syntactic sisters. We show how our analysis deals with four illustrative cases: the indefinite article alternation in English, syncretic liaison forms for possessive pronouns in French, Hausa verb-final vowel shortening, and soft mutation in Welsh nouns.
Enhanced Latent Heating over the Tibetan Plateau as a Key to the Enhanced East Asian Summer Monsoon Circulation under a Warming Climate

Coupled climate system models consistently show that the low-level southerly wind associated with the East Asian summer monsoon (EASM) is enhanced under anthropogenic greenhouse gas forcing, and the enhanced EASM was attributed to the enhanced land–sea thermal contrast by previous studies. Based on a comparison of the global warming scenarios with the present-day climate in an ensemble of 30 coupled models from phase 5 of the Coupled Model Intercomparison Project (CMIP5), we show evidence that changes in land–sea thermal contrast cannot explain the enhanced EASM circulation in terms of the seasonality. Indeed, the enhanced low-level southerly wind over East Asia is associated with a large-scale anomalous cyclone around the Tibetan Plateau (TP), and numerical simulation by the Linear Baroclinic Model suggests that the enhanced latent heating over the TP associated with enhanced precipitation is responsible for this low-level cyclone anomaly and the enhanced EASM circulation projected by the coupled models. Moisture budget analysis shows that enhanced hydrological recycling and enhanced vertical moisture advection due to increased specific humidity have the largest contribution to the increased precipitation over the TP, and more than half of the intermodel uncertainty in the projected change of EASM circulation is associated with the uncertainty in the changes of precipitation over the TP. Therefore, the TP plays an essential role in enhancing the EASM circulation under global warming through enhanced latent heating over the TP.
Finer Granularity Clustering for Opinion Mining

The boom of opinion-rich resources such as online review websites, discussion groups, personal blogs and forums on the web has attracted many research efforts on opinion mining. Positive and negative opinions represented in review documents are helpful information for governments to improve their services, for companies to market their products, and for customers to purchase their commodities. In this paper, we introduce a new approach that employs finer granularity clustering for opinions extraction and clustering for the calculation of their sentiment orientation of opinions. The experimental result shows that the approach is qualitatively quite useful when used to analyze the netizens’ opinions to hot topics from some websites.
A Bottom-up Approach to Data Annotation in Neurophysiology

Metadata providing information about the stimulus, data acquisition, and experimental conditions are indispensable for the analysis and management of experimental data within a lab. However, only rarely are metadata available in a structured, comprehensive, and machine-readable form. This poses a severe problem for finding and retrieving data, both in the laboratory and on the various emerging public data bases. Here, we propose a simple format, the “open metaData Markup Language” (odML), for collecting and exchanging metadata in an automated, computer-based fashion. In odML arbitrary metadata information is stored as extended key–value pairs in a hierarchical structure. Central to odML is a clear separation of format and content, i.e., neither keys nor values are defined by the format. This makes odML flexible enough for storing all available metadata instantly without the necessity to submit new keys to an ontology or controlled terminology. Common standard keys can be defined in odML-terminologies for guaranteeing interoperability. We started to define such terminologies for neurophysiological data, but aim at a community driven extension and refinement of the proposed definitions. By customized terminologies that map to these standard terminologies, metadata can be named and organized as required or preferred without softening the standard. Together with the respective libraries provided for common programming languages, the odML format can be integrated into the laboratory workflow, facilitating automated collection of metadata information where it becomes available. The flexibility of odML also encourages a community driven collection and definition of terms used for annotating data in the neurosciences.
Associative document retrieval by query subtopic analysis and its application to invalidity patent search

We propose an associative document retrieval method, in which a document is used as a query to search for other similar documents. Because a long document usually includes more than one topic, we first analyze a query document to extract multiple subtopics. For each subtopic element, a sub-query is produced and similar documents are retrieved with a relevance score. The relevance scores are weighted by the importance of each subtopic element and are integrated to determine the final relevant documents. In the calculation of the subtopic importance, the specificity of a query term is evaluated using entropy, which is the deviation degree of the appearances of the term in each subtopic element. We apply this method to an invalidity patent search. By exploiting certain unique features of Japanese patent claims, we use features distinguishing the preamble and the essential portion in a query patent claim. To demonstrate the effectiveness of our method, we experimentally evaluated our associative document retrieval method on five years of patent documents.
21.7 A 1.8mW PLL-free channelized 2.4GHz ZigBee receiver utilizing fixed-LO temperature-compensated FBAR resonator

This paper presents an ultra-low-power 2.4GHz receiver for the IEEE 802.15. 4 (ZigBee) standard. Traditional short-range ISM-band radios require a PLL-based frequency synthesizer for channelization across the band of interest [1-3]. The lowest ZigBee power consumption found in the literature to date is 1.6mW (RX) and 1.8mW (PLL) by employing a sliding-IF architecture [1]. [4] proposes a BAW-based 2.4GHz ZigBee receiver that saves power by eliminating the off-chip quartz crystal with super-high IF architecture; however, 8.2mW DC power is consumed since a low frequency LC-PLL is necessary for channel select tuning. The Blixer in [5] reduced the RX DC power through current re-use; however, the LO generator suffers from high power consumption due to the high-frequency quadrature LO.
1,1′-Bicyclohexyl-1,1′-diyl 2,2′-bipyridine-3,3′-dicarboxylate

The title compound, C24H26N2O4, lies about a crystallographic twofold rotation axis. The cyclohexane rings adopts a chair conformation. The two pyridine rings form a dihedral angle of 41.02 (4)°. In the crystal, molecules are linked via C—H⋯O and C—H⋯N hydrogen bonds into a layer parallel to the bc plane.