Miracle-dz/UniFAR-FTUs huggingface dataset:
Der Komparativzyklus und die Position der Vergleichspartikeln

This paper discusses the syntactic position of comparative particles in German against the background of their diachrony. The development that these particles undergo is shown to constitute an instance of cyclical change, the comparative cycle. The historical data, especially so-called hypothetic comparisons, provide evidence for a synchronic analysis of als as a syntactic head above the standard of comparison-CP, and wie as C 0 . It is argued that, diachronically, the former has changed from a lower to a higher syntactic head position while the latter has undergone a reanalysis from a specifier to a head.
Influence of auxins on somatic embryogenesis in Haworthia retusa Duval

An efficient in vitro plant regeneration method through somatic embryogenesis has been established in Haworthia retusa. Somatic embryos were induced from leaf explants on Murashige and Skoog (MS) medium supplemented with different concentrations of 2,4-dichlorophenoxyacetic acid (2,4-D), indole-3-acetic acid (IAA), indole-3-butyric acid (IBA), and α-naphthaleneacetic acid (NAA) either alone or in combination with 4 μM thidiazuron (TDZ). Of the four auxins studied, IBA was found to be the most promising in terms of somatic embryo induction, followed in decreasing frequency by 2,4-D, IAA, and NAA. The highest somatic embryo induction (60.7%), with a mean of 20.7 embryos per leaf explant, was observed on MS medium amended with 20 μM IBA. The inclusion of 4 μM TDZ to the auxin-containing medium significantly (p < 0.0001) increased the somatic embryo induction frequency as well as the number of somatic embryos. The best combination for somatic embryogenesis was IBA + TDZ. The highest incidence of somatic embryo induction (100%), with a mean of 55.8 somatic embryos, was obtained on a culture medium containing 16 μM IBA + 4 μM TDZ. Somatic embryos germinated best on MS medium supplemented with 2 μM gibberellic acid. Morphological variations were observed among the regenerated plantlets. Well-developed plantlets obtained from germination media were acclimatized in the greenhouse.
On automatic synthesis of analog/digital circuits

The paper builds on a recent explicit numerical algorithm for Kolmogorov`s superpositions, and will show that in order to synthesize minimum size (i.e., size-optimal) circuits for implementing any Boolean function, the nonlinear activation function of the gates has to be the identity function. Because classical and--or implementations, as well as threshold gate implementations require exponential size, it follows that size-optimal solutions for implementing arbitrary Boolean functions can be obtained using analog (or mixed analog/digital) circuits. Conclusions and several comments are ending the paper.
Multihop Multi-band Cognitive Architecture for Next Generation Cellular Networks

Lately, due to to the tremendous success of mobile communications, the cellular band is very crowded while a large portion of the electromagnetic spectrum assigned for other services is used sporadically. Cognitive Radio is seen as a new communication paradigm to exploit the existing radio spectrum opportunistically to improve the utilization of the radio spectrum. In this paper, a novel multihop multi-band cognitive radio architecture for cellular network is proposed which makes use of a number of cognitive gateways in order to enable simultaneous usage of spectrum resources within the same cell. It is mathematically demonstrated that the carrier-to-interference ratio is maximized when there are six cognitive gateways placed equidistantly from each other. This two-hop cognitive architecture provides a significant increase in the system capacity and exponentially decreases the resource allocation delay, as compared to single-hop and a standard two-hop routing technique.
Cross-layer efforts for energy-efficient computing: towards peta operations per second per watt

As Moore’s law based device scaling and accompanying performance scaling trends are slowing down, there is increasing interest in new technologies and computational models for fast and more energy-efficient information processing. Meanwhile, there is growing evidence that, with respect to traditional Boolean circuits and von Neumann processors, it will be challenging for beyond-CMOS devices to compete with the CMOS technology. Exploiting unique characteristics of emerging devices, especially in the context of alternative circuit and architectural paradigms, has the potential to offer orders of magnitude improvement in terms of power, performance, and capability. To take full advantage of beyond-CMOS devices, cross-layer efforts spanning from devices to circuits to architectures to algorithms are indispensable. This study examines energy-efficient neural network accelerators for embedded applications in this context. Several deep neural network accelerator designs based on cross-layer efforts spanning from alternative device technologies, circuit styles, to architectures are highlighted. Application-level benchmarking studies are presented. The discussions demonstrate that cross-layer efforts indeed can lead to orders of magnitude gain towards achieving extreme-scale energy-efficient processing.
Epidural catheter infections.

Epidural analgesia is used as a method of pain relief throughout the UK. It is used short-term in obstetric practice, following surgery and after trauma, and also longer-term for malignancy and chronic pain. Infection may occur as a complication of the technique. Both deep infection, e.g., meningitis, paraspinal and epidural abscesses, and superficial skin infections can occur. To minimize infection risk, epidural catheters should be inserted using an aseptic technique and subsequently checked at least daily, looking for evidence of superficial and deep infection. There should be a dedicated pain team to ensure that education of staff occurs and to carry out regular audits of the service.
Smartphone tools for anaphylaxis management

Anaphylaxis is a severe life-threatening allergic condition which is increasing in prevalence and now affects more than 2% of UK children. Anaphylaxis management requires the avoidance of allergen triggers and preparation in readiness for an anaphylactic reaction. People with anaphylaxis and their carers carry Adrenaline Auto-Injectors which need to be administered immediately in the event of an anaphylactic reaction. But, unfortunately, many people often do not know how to use the injectors and fail to use them or fail to use them correctly. This is due in part to deficiencies in training and also to a lack of a system encouraging continuous practice and providing feedback on that practice. Pervasive healthcare research has demonstrated potential in supporting the management of chronic conditions such as diabetes. However, research into assistive technologies for the support of anaphylaxis management has been significantly neglected. Thesis results provide evidence of the potential that smartphone tools have to significantly improve adrenaline injection training skills and a positive influence on self-efficacy. In addition, the results provide insights into possible self-efficacy failings in traditional training and benefits of embedding self-efficacy theory into the design process. The thesis also shows that clinical staff expressed positive feedback after they were provided the technology for one week.
A model of joint attention for humans and machines

Joint attention is the simultaneous allocation of attention to a target as a consequence of attending to each other’s attentional states. It is an important prerequisite for successful interaction and supports the grounding of future actions. Cognitive modeling of joint attention in a virtual agent requires an operational model for behavior recognition and production. To this end, we created a declarative four-phase-model (initiate / respond / feedback / focus) of joint attention based on a literature review. We applied this model to gaze communication and implemented it in the cognitive architecture of our virtual agent Max. To substantiate the model regarding the natural timing of gaze behavior, we conducted a study on human-agent interactions in immersive virtual reality. The results show that participants preferred the agent to exhibit a timing behavior similar to their own. Building on these insights, we now aim at a process model of joint attention. We are interested in patterns of joint attention emerging in natural interactions. In the preliminary results of a human-human study, we find patterns of fixation targets and fixation durations that allow us to identify the four phases and infer the current state of joint attention.
Maximum RPM-Taking the Red Hat Package Manager to the Limit

Fishing apparatus for use with a trolled fishing lure having on one end a fish lure and on the other end a stop, comprising a trolled line support and receiving means positioned on the support for releasably retaining the stop in the trolling position of the line. A reel is mounted for rotation in a predetermined station relative to the support. Stop receiving means is present on the reel for releasably retaining the stop in the retrieving position of the line. When a fish strikes, the trolled line is transferred from the support to the reel, and reeled in.
Developing communities of practice in the NeLH (National electronic Library for Health)

Urquhart, C. , Yeoman, A. , Sharp, S. (2003). Developing communities of practice in the NeLH (National electronic Library for Health). In Proceedings of the UKAIS (UK Academy for Information Systems) annual conference, University of Warwick, April 2003. Sponsorship: NHS Information Authority/National electronic Library for Health
Towards the implementation of vision-based UAS sense-and-avoid

Machine vision represents a particularly attractive solution for sensing and detecting potential collision-course targets due to the relatively low cost, size, weight, and power requirements of the sensors involved. This paper describes the development of detection algorithms and the evaluation of a real-time flight ready hardware implementation of a vision-based collision detection system suitable for fixed-wing small/medium size UAS. In particular, this paper demonstrates the use of Hidden Markov filter to track and estimate the elevation (β) and bearing (α) of the target, compares several candidate graphic processing hardware choices, and proposes an image based visual servoing approach to achieve collision avoidance
Extending the boolean and vector space models of information retrieval with p-norm queries and multiple concept types

Information retrieval systems accept user queries and respond by identifying documents presumed to be relevant to those queries. Boolean logic is commonly employed as the query language, but an alternate scheme based on the vector space model has been investigated. Automatic indexing methods allow questions and documents to be represented by weighted vectors, and searching yields a ranked list of documents in decreasing order of query-document similarity. Both the Boolean logic and vector space approaches are special cases of the very general p-norm model developed by Wu. In this thesis, analytical results help explain the ranking behavior of p-norm queries. Four experimental test collections are employed to prove that interpreting Boolean queries with p-norm techniques leads to substantial improvements in retrieval effectiveness. Several procedures are described to automatically construct Boolean queries from short lists of words. An algorithm based on probability theory which utilizes relevance feedback information to produce even more effective Boolean or p-norm queries is also specified and validated by experimental tests; one of the essential innovations is to control query construction by allowing the searcher to specify the desired number of retrieved documents. The vector space model is extended to allow separate handling of other types of concepts beyond those derived from textual words or assigned descriptors. Citation, cocitation, and bibliographic coupling data as well as factual information normally handled by database management systems are easily incorporated. Clustered search and feedback processes are improved by utilizing combinations of these concept types, as shown by preliminary experimental studies with collections in computer and information science. P-norm queries and multiple concept types are both handled by an updated SMART system implemented using relational database and statistical processing packages. This integrated system should facilitate further research as well as be adaptable to retrieval applications for office and bibliographic information.
Effects of Branch Predictors on Execution Time

This technical report describes the result of a short experimental investigation into the effect of branch predictors on the execution times of tight loops on modern aggressive microprocessors. The same code was tried on Pentium III, Athlon, UltraSparc II, and UltraSparc III processors. For reference, the same experiment was carried out on a simple V850E processor to determine the behavior without branch prediction. The results indicate that advanced branch predictors give a very high and hard-to-understand variation in the execution time of loops, and that this effect can be very big relative to the execution time of other instructions.
On Some Methods for Improving Feature Vectors for Web Pages and their Retrieval Accuracy

In IR (information retrieval) systems based on the vector space model, the tf-idf scheme is widely used to characterize doc- uments. However, in the case of documents with hyperlink structures such as Web pages, it is necessary to develop a technique for representing the contents of Web pages more accurately by exploiting that of their hyperlinked neighboring pages. In this paper, we first propose some methods for improving the tf-idf scheme for a target Web page by using the contents of its hyperlinked neighboring pages, and then compare retrieval accuracy of our proposed methods. Experimental results show that more accurate feature vectors of a target Web page can be generated in the case of utilizing the contents of its hyperlinked neighboring pages at levels up to second in the backward direction from the target page.
Anomaly detection in dynamic execution environments

In the past few years, languages which run on virtual machines, like Java and C#, have become popular. These are platforms as well as languages, and they are characterized by being verifiable and garbage collected, and include Just-In-Time compilers, large standard libraries, and runtime profilers. I call platforms with these features dynamic execution environments (DEEs). The runtime infrastructure of DEEs allows access to features of execution that were previously difficult to observe. My research consists of a series of case studies in which I build systems to classify behavior of a particular feature into normal and abnormal and then use that classification for either security or optimization purposes. These systems are anomaly detectors. I build anomaly detection systems for method invocations, permissions, and method invocation sequences. I call them dynamic sandboxes, and they are they are used to detect intrusions or system faults. I also show that an anomaly detector can be used to predict object lifetimes resulting in an improved garbage collector.
Robust Robot Grasp Detection in Multimodal Fusion

Accurate robot grasp detection for model free objects plays an important role in robotics. With the development of RGB-D sensors, object perception technology has made great progress. Reach feature expression by the colour and the depth data is a critical problem that needs to be addressed in order to accomplish the grasping task. To solve the problem of data fusion, this paper proposes a convolutional neural networks (CNN) based approach combined with regression and classification. In the CNN model, the colour and the depth modal data are deeply fused together to achieve accurate feature expression. Additionally, Welsch function is introduced into the approach to enhance robustness of the training process. Experiment results demonstrates the superiority of the proposed method.
Electromagnetically braked versus mechanically braked cycle ergometers: Effects of aerobic power and total physical workloads

OBJECTIVE: To determine the differences in physiological performance at constant submaximal load and aerobic power levels of electromagnetically and mechanically braked cycle ergometers. METHOD: Nineteen trained male athletes who specialize in cycling and triathlons participate in this study (age, 20.21 ± 3.50 years; body mass, 73.36 ± 13.19 kg; height, 178.73 ± 8.54 cm). A randomized cross-over study design was used to compare a mechanically braked Monark cycle ergometer (MCE) and an electromagnetically braked Lode Excalibur cycle ergometer (ECE). After the V O2max test, total physical work capacity and work efficiency (GE) were analysed during 60% of V O2max constant loading submaximal tests with MCE and ECE. A paired sample t-test was used to compare V O2max and constant loading submaximal test data of the ergometers. RESULTS: Applying the ECE system resulted in a significantly higher V O2max value (9.3%; p = 0.004), similar respiratory exchange ratio value (1.8% lower; p = 0.290), similar power output at exhaustion point (1% higher; p = 0.620), significantly higher total energy expenditure at exhaustion point and mean cadence (Cadmean) value (12%; p = 0.025, 9.6%; p = 0.000) respectively. In the constant loading submaximal tests, however, significant differences were found in mean power output (p = 0.013), Cadmean (p = 0.000), and GE (p = 0.000) values. CONCLUSION: Since the ECE system was associated with a higher V O2max and allowed test performance at the expected V O2 consumption at constant submaximal loads, we recommend using the ECE for determination of aerobic power and total physical workloads.
Mitigating Limited PCM Write Bandwidth and Endurance in Hybrid Memory Systems

With the rise of big data and cloud computing, there is increasing demand on memory capacity to solve problems of large sizes and consolidate computation tasks. For large capacity memory systems, DRAM is a significant source of energy consumption. Non-volatile memory, such as Phase-Change Memory (PCM), is a promising technology for constructing energy-efficient memory. Unlike DRAM, PCM has negligible background (static) power and allows high density packaging. But PCM also has limited write bandwidth and write endurance. Hybrid memory systems have been proposed to combine the high-density and low standby power of PCM with the good write performance of DRAM. This thesis addresses two challenges which are unique to hybrid memory systems. The first challenge is the limited PCM bandwidth, which can become a performance bottleneck. The second challenge is the non-contiguous physical memory due to retired memory pages. Since PCM cells have limited write endurance, it is inevitable to gradually have increased number of uncorrectable errors during the lifetime. Memory pages that have detected errors are normally retired by the OS, which create unusable “holes” in the physical memory. These unusable holes make it difficult to construct traditional superpages, which can incur significant performance overhead. In this thesis, I propose three solutions to address these two challenges. First, I observed that an unbalanced distribution of modified data bits among PCM chips significantly increases PCM write time and hurts effective write bandwidth. I propose new XOR-based mapping schemes between program data bits and PCM cells to improve PCM write throughput by spreading modified data bits evenly among PCM chips. Second, I propose a compressed DRAM cache scheme to improve DRAM effective capacity and reduce write traffic to PCM. A new adaptive delta-compression technique for modified data is used to achieve a large compression ratio. Third, I propose Gap-tolerant Sequential Mapping, a new memory page mapping scheme, to construct superpages from non-contiguous physical memory. The proposed three solutions have simple and practical designs, and can be easily adopted in future hybrid memory systems.
Statistical Properties for Multiparadigm Pattern Recognition

Recently, expectations about monitoring and control systems for complex industrial production lines are becoming ever more severe. Modern production lines are characterized by a variety of heterogeneous processing units, controlled by embedded microprocessors or remotely controllable through digital telecommunication links. In industrial scenarios where rapid process dynamics, scarce knowledge of the phenomena determining the final features of the workpiece, and high noise are the norm, observing and controlling the process to keep it in its optimal window is a challenging task, especially in the applicative scenarios where this control must be achieved in real time. Current research is focusing on the definition of novel processing units where a set of heterogeneous environmental sensors monitors the process while in progress. The obtained sensor data are preprocessed and reduced to a set of meaningful synthetic features. These features may feed an online process monitoring and control system. Such an arrangement can be effective provided that, on one side, the sensors convey relevant and sufficient information, and on the other side that this information can effectively be leveraged to recognize or even anticipate the phenomena happening within the process. When a model of the process is not available, both the conditions are hardly met. In this situation, inductive methods which implicitly build a model of the relevant phenomena from the available data are the only practical alternative. Nowadays the system designer can choose from many inductive methods, ranging from Fisher linear discriminant to neural networks to genetic algorithms, each suitable to one
Higher-Order Clustering in Heterogeneous Information Networks

As one type of complex networks widely-seen in real-world application, heterogeneous information networks (HINs) often encapsulate higher-order interactions that crucially reflect the complex nature among nodes and edges in real-world data. Modeling higher-order interactions in HIN facilitates the user-guided clustering problem by providing an informative collection of signals. At the same time, network motifs have been used extensively to reveal higher-order interactions and network semantics in homogeneous networks. Thus, it is natural to extend the use of motifs to HIN, and we tackle the problem of user-guided clustering in HIN by using motifs. We highlight the benefits of comprehensively modeling higher-order interactions instead of decomposing the complex relationships to pairwise interaction. We propose the MoCHIN model which is applicable to arbitrary forms of HIN motifs, which is often necessary for the application scenario in HINs due to their rich and diverse semantics encapsulated in the heterogeneity. To overcome the curse of dimensionality since the tensor size grows exponentially as the number of nodes increases in our model, we propose an efficient inference algorithm for MoCHIN. In our experiment, MoCHIN surpasses all baselines in three evaluation tasks under different metrics. The advantage of our model when the supervision is weak is also discussed in additional experiments.
Bioconductor’s nnNorm package

The nnNorm package provides utilities to detect and correct for spatial bias with two color DNA microarrays (or paired single channel data). The normalization implemented in nnNorm package is based on neural networks models. Functionality to compare the distributions of the normalized log ratios is also provided. For the simpler case when only intensity normalization is desired (univariate distortion color model, similar to print tip loess normalization), we provide functionality to plot the bias estimate against the level of intensity for every print tip group.