Miracle-dz/UniFAR-FTUs huggingface dataset:
Perceived and reported romantic and sexual outcomes in long-distance and geographically close relationships

Abstract:More and more young people are in long-distance relationships (LDRs). However, little is known about perceived or reported outcomes of LDRs compared to geographically close relationships (GCRs). This investigation compared the relationship outcomes (Study 1) and perceived outcomes (Study 2) of individuals in LDRs and GCRs. In Study 1, young adults in LDRs (n = 232) and GCRs (n = 263) completed an online survey assessing relationship and sexual outcomes (romantic satisfaction, sexual satisfaction, extradyadic sexual activity); individuals in LDRs also rated the positive and negative impacts of being in an LDR. Individuals in LDRs and GCRs had similar satisfaction, a similar likelihood of engaging in extradyadic sexual activity, and perceived the impact of being in an LDR as more positive than negative. In Study 2, young adults (N = 626) recruited online were randomly assigned to rate the same outcomes for a hypothetical couple in an LDR or GCR. Observers perceived being in an LDR as having a more negative than positive impact on the sexual relationship. However, satisfaction ratings for both LDRs and GCRs were high although individuals in LDRs were perceived as having significantly lower satisfaction than reported in Study 1. Few gender differences emerged, and perceptions were not affected by participants' past experience being in an LDR. Overall, the results suggest that outcomes for LDRs and GCRs are similar and that people have generally positive perceptions of LDRs. These results have positive implications for young adults, given the popularity of LDRs in this age group.
Changing ceramic traditions at Agila ancestral village, Hood Bay, Papua New Guinea

Abstract Accounts of New Guinea’s recent past are replete with both archaeological and ethnographic evidence of trade that indirectly connect virtually the entire country from coast to highland. One consequence has been a bias towards central places (e.g. Mailu Island) and/or large-scale production villages (e.g. of the Port Moresby region) as origin locations for distributed goods. Inversely, there has also been attention paid to distant, recipient points in the landscape (e.g. Gulf of Papua lowlands) where incoming traders turn back home to their originating villages. Less attention has been given to those extreme edges where separate networks indirectly connect. Here we present new evidence from Hood Bay on the south coast of PNG, a region that lies at a crossroads between the west-sailing Motu hiri and eastern Mailu Island ceramicists and seafaring traders. By being on the margins of each, Hood Bay is geographically well positioned to investigate changing inter-regional seafaring networks along a broad coastal expanse. We present initial results from excavations at the Agila village site, Hood Bay, where a changing incidence of western Motu and Mailu ceramics is evident. The results signal that Hood Bay villagers reorganised alliances and access to commodities and influence, depending on the prevailing conditions beyond their immediate western and eastern horizons.
Complexity analysis of the fetal heart rate for the identification of pathology in fetuses

Monitoring of fetal conditions is a very important step to assure a healthy newborn state. A special interest is reserved to Intrauterine Growth Restricted (IUGR) fetuses in the very preterm period, when the interpretation of fetal examinations is often very difficult. In order to study the fetal heart rate complexity we have introduced the Lempel-Ziv (LZ) complexity parameter as a global index estimating unpredictability level of the time series. We have compared this new parameter with other regularity estimators: Approximate Entropy and Sample Entropy. The results show that the LZ complexity is a stable parameter and its value significantly discriminates the severe IUGR (preterm delivered) from the not severe IUGR (at term delivered) and normal fetuses. The introduction of the LZ complexity parameter could improve the diagnostic ability of the fetal monitoring systems
Transmit beampattern synthesis using eigenvalue decomposition in MIMO radar

MIMO radar is the next generation radar which transmits arbitrary waveforms at each one of its apertures. It has been shown that design of waveforms for MIMO radars in order to synthesize a desired spatial beampattern is mapped into a waveform correlation matrix (R) design in the narrowband case. Searching for desired R has been modeled as a convex optimization problem which demands considerable processing power. There are also some close form solutions for special cases like rectangular beampatterns. Here we deal with the problem from a matrix eigenvalue theory perspective and show how close form solutions can be found for more general cases relaxing high computational power demand. Our proposed method also fulfills uniform elemental power, targets decorrelation and low Side Lobe Level.
Transcriptomic Analysis of Tea Plant Responding to Drought Stress and Recovery

Tea plant (Camellia sinensis) is an economically important beverage crop. Drought stress (DS) seriously limits the growth and development of tea plant, thus affecting crop yield and quality. To elucidate the molecular mechanisms of tea plant responding to DS, we performed transcriptomic analysis of tea plant during the three stages [control (CK) and during DS, and recovery (RC) after DS] using RNA sequencing (RNA-Seq). Totally 378.08 million high-quality trimmed reads were obtained and assembled into 59,674 unigenes, which were extensively annotated. There were 5,955 differentially expressed genes (DEGs) among the three stages. Among them, 3,948 and 1,673 DEGs were up-regulated under DS and RC, respectively. RNA-Seq data were further confirmed by qRT-PCR analysis. Genes involved in abscisic acid (ABA), ethylene, and jasmonic acid biosynthesis and signaling were generally up-regulated under DS and down-regulated during RC. Tea plant potentially used an exchange pathway for biosynthesis of indole-3-acetic acid (IAA) and salicylic acid under DS. IAA signaling was possibly decreased under DS but increased after RC. Genes encoding enzymes involved in cytokinin synthesis were up-regulated under DS, but down-regulated during RC. It seemed probable that cytokinin signaling was slightly enhanced under DS. In total, 762 and 950 protein kinases belonging to 26 families were differentially expressed during DS and RC, respectively. Overall, 547 and 604 transcription factor (TF) genes belonging to 58 families were induced in the DS vs. CK and RC vs. DS libraries, respectively. Most members of the 12 TF families were up-regulated under DS. Under DS, genes related to starch synthesis were down-regulated, while those related to starch decomposition were up-regulated. Mannitol, trehalose and sucrose synthesis-related genes were up-regulated under DS. Proline was probably mainly biosynthesized from glutamate under DS and RC. The mechanism by which ABA regulated stomatal movement under DS and RC was partly clarified. These results document the global and novel responses of tea plant during DS and RC. These data will serve as a valuable resource for drought-tolerance research and will be useful for breeding drought-resistant tea cultivars.
Design of multicarrier pulses maximizing SINR by ISI/ICI shaping for the Doubly Dispersive channel

Multicarrier modulation (MCM) is a popularly used transmission technique. This paper aims at designing the multicarrier modulation pulse for communication over a Doubly Dispersive (DD) channel. For a DD channel, Inter Symbol Interference (ISI)\Inter Carrier Interference (ICI) can be completely eliminated only when we design the pulses with the knowledge of the channel state. But for a quickly varying doubly dispersive channel, the channel state cannot be tracked by the transmitter. So instead of designing a pulse which suppresses all the ISI\ICI, the proposed technique designs the MCM pulses which allows a tolerable ISI\ICI within the target pattern and eliminates all the ISI\ICI outside the target pattern. By properly selecting the target pattern, it is possible to treat the allowed ISI\ICI by using simple equalization/decoding techniques.
1 Evolutionary Perspectives on Firms ’ Internal and External Portfolios of New Capabilities

Received wisdom from evolutionary theory and behavioral approaches yields potentially heterogeneous search pathways for firms under uncertain conditions. On one hand, the need for experimentation under uncertainty propels firms to initiate a broad-based search, followed by the selection and retention of a narrow set of capabilities as learning occurs. We label this search pathway as 'outside-in' wherein variety is followed by focus. On the other hand, behavioral assumptions of cognitive constraints and routines point to a focused set of capabilities, which broaden as firms build absorptive capacity over time. Moreover, path dependence can render the search process inflexible making selective retention more difficult. We label this alternative search pathway as 'inside-out' wherein focus is followed by variety. We find support for these two alternative search pathways in a radical technological context: 'inside-out' and 'outside-in' characterizing firms' internal and external portfolios of capabilities, respectively. We reason that as learning occurs, firms' internal portfolios are reconfigured less easily relative to external portfolios constituting more loosely coupled arrangements such as alliances. Our theory and empirical findings hold important implications for understanding firms' technology strategy and innovation performance in an evolving technological context.
Classification of Mammographic images using Gabor Wavelet and Discrete Wavelet Transform

—Breast cancer is the most commonly occurring cancer in women. Early detection of breast cancer is important step in diagnosis of the abnormalities which may reduce the mortality rate. It can be achieved using digital mammography. Mammography is most reliable and widespread method for early detection of breast cancer. The proposed system has three major steps-Preprocessing, Feature Extraction and Classification. The Preprocessing stage involves image acquisition and image enhancement using Histogram equalization and median filter. Feature extraction methodologies analyze objects and images to extract the most prominent features that represent various classes of objects. Gabor Wavelet based features are used as inputs to classifier that assign them to the class that they represent. For comparison Discrete Wavelet Transform (DWT) is applied. Once features are extracted, Principal Component Analysis (PCA) is applied to it for dimensionality reduction. Finally, the extracted features are fed as input to the Support Vector Machine Classifier (SVM) which classifies the images into normal or abnormal (benign or malignant) images. The classifier is applied to a database of 322 images, originating from the MIAS database.
Life-Cycle Assessment, Implementation and Use in Swedish Industry

Environmental concern has greatly increased in magnitude within the companies of Swedish industry. Product development has become a strategic area: the environmental adaptation of products is fundamental for a decrease in environmental impact from human activities, and product development is an area of the greatest importance to the competitiveness of companies. Integrating environmental aspects into product development at operations level is needed to achieve product improvements. The theme of this thesis is how to integrate environmental aspects into product development. An overarching purpose has been to identify adequate activities and changes required for integration. Great importance has been attached to conducting changes, especially by investigating how successfully to implement support tools in product development. Qualitative research interviews have been used to collect empirical data. Conclusions on measures industrially applicable to enabling the integration of environmental aspects have been drawn, as empirical data and experiences have been accumulated. Environmental aspects give rise to new considerations in product development: causal relationships between products and environmental impact; the life-cycle approach; and, new priorities and trade-offs between function, cost and quality of products. A need for activities supporting these considerations is identified; and, preferably, several activities, concerning knowledge development, work procedures and support tools, should be applied. It is also important to identify environmental actors for providing expertise and enthusiasm in the organisation. The implementation of support tools has to be carefully considered. To guide such implementation a framework with key factors has been developed. The framework suggests a cyclical implementation process, identification of the organisational change field, and consistent management behaviour. Keys to successful implementation are goal setting, knowledge development, adequate resources, anchoring at all levels, and a focus on individuals. To stay competitive, companies need to be proactive and respond to the driving forces underlying environmental adaptation. To make possible the environmental adaptation of products, several measures are needed. The following proactive measures have been identified: Management ought to set direction with a comprehensive view on business development and physical flows in the business. Commitment to desired change must be created to make sure changes are accepted and durable. Knowledge and skills need to be developed with an action learning approach. Work procedures need to be adjusted to include environmental criteria and secure interaction between product developers and environmental experts. Support tools can support a structured approach and enable rapid progress to be attained.
Machine Learning Techniques for Word Sense Disambiguation

In the Natural Language Processing (NLP) community, Word Sense Disambiguation (WSD) has been described as the task which selects the appropriate meaning (sense) to a given word in a text or discourse where this meaning is distinguishable from other senses potentially attributable to that word, These senses could be seen as the target labels of a classification problem. That is, Machine Learning (ML) seems to be a posible way to tackle this problem. This work studies the possible application of the algorithms and techniques of the Machine Learning field in order to handle the WSD task. The first issue treated has been the adaptation of alternative ML algorithms to deal with word senses as classes. Then, a comparison of these methods is performed under the same conditions. The evaluation measures applied to compare the performances of these methods are the typical precision and recall, but also agreement rates and kappa statistics. The second topic explored is the cross-corpora application of supervised Machine Learning systems for WSD to test the generalisation ability across corpora and domains. The results obtained are very disappointing, seriously questioning the possibility of constructing a general enough training corpus (labelled or unlabelled), and the way its examples should be used to develop a general purpose Word Sense Tagger. The use of unlabelled data to train classifiers for Word Sense Disambiguation is a very challenging line of research in order to develop a really robust, complete and accurate Word Sense Tagger. Due to this fact, the next topic treated in this work is the application of two bootstrapping approaches on WSD: the Transductive Support Vector Machines and the Greedy Agreement bootstrapping algorithm by Steven Abney. During the development of this research we have been interested in the construction and evaluation of several WSD systems. We have participated in the last two editions of the English Lexical Sample task of Sen
Key management and secure software updates in wireless process control environments

Process control systems using wireless sensor nodes are large and complex environments built to last for a long time. Cryptographic keys are typically preloaded in the wireless nodes prior to deployment and used for the rest of their lifetime. To reduce the risk of successful cryptanalysis, new keys must be established (rekeying). We have designed a rekeying scheme that provides both backward and forward secrecy. Furthermore, since these nodes are used for extensive periods of time, there is a need to update the software on the nodes. Different types of sensors run different types and versions of software. We therefore establish group keys to update the software on groups of nodes. The software binary is split into fragments to construct a hash chain that is then signed by the network manager. The nodes can thus verify the authenticity and the integrity of the new software binary. We extend this protocol by encrypting the packets with the group key such that only the intended receivers can access the new software binary.
Weak Probabilistic Bisimulation for Secure Information Flow

This paper proposes a notion of weak probabilistic bisimulation for Markov chains and shows how it can be used to justify the correctness of a recentlypublished type system for secure information flow. The type system guarantees that well-typed multi-threaded programs running under a uniform probabilistic scheduler satisfy the probabilistic noninterference property.
Using Optimization Method to Determine the Dynamic Recrystallization Kinetics of Q235

A coupled mathematical model based on dislocation theory is presented in the paper. It is applied to evaluation of the dynamic recrystallization kinetics using optimization method. The model does not distinguish different kinds of recrystallization, which are considered as the same process rooted in nucleation and grain growth. And the dynamic recrystallization fraction is related to the flow stress by formulations, which includes dislocation density. Flow stress is calculated by the dislocation density. The dislocation density formula takes into accounts hardening, recovery and recrystallization during the hot deformation process. In the model the variables changes are introduced by ordinary differential equations. Model parameters are defined from comparison of the calculated curves with the measured flow stress curves. That is finished through solving the nonlinear least-squares problem. Finally, in order to validate the obtained parameters, the kinetics for dynamic recrystallization obtained by the proposed model were compared with that in the literature obtained using another approach.
A task-based security model to facilitate collaboration in trusted multi-agency networks

Security problems in collaboration work are less well understood than those in the business and defence worlds. Earlier work in the medical area in Britain has highlighted some of the principles involved but has neglected some important areas. Most of the security models developed to date are inadequate in the collaboration area. We develop a perspective for policies and models that is task-based on a need-to-know basis. These policies can be represented as Petri nets to identify the functions and states involved. We have also developed a general architecture for a secure collaborative environment. An example is given of the application of our techniques to a problem involving negotiation, decision and agreement in a collaboration environment.
Chameleonic Theories: A Short Review

In the chameleon mechanism, a field (typically scalar) has a mass that depends on the matter density of the environment: the larger is the matter density, the larger is the mass of the chameleon. We briefly review some aspects of chameleonic theories. In particular, in a typical class of these theories, we discuss the lagrangian, the role of conformal transformations, the equation of motion and the thin-shell effect. We also discuss $f(R)$ theories and chameleonic quantum gravity.
Spatially Resolved Chemistry in Nearby Galaxies. I. The Center of IC 342

We have imaged emission from the millimeter lines of eight molecules—C2H, C34S, N2H+, CH3OH, HNCO, HNC, HC3N, and SO—in the central half-kiloparsec of the nearby spiral galaxy IC 342. The 5'' (~50 pc) resolution images were made with the Owens Valley Millimeter Array. Using these and previously published CO and HCN images, we obtain a picture of the chemistry within the nuclear region on the size scales of individual giant molecular clouds. Bright emission is detected from all but SO. There are marked differences in morphology for the different molecules. A principal-component analysis is performed to quantify similarities and differences among the images. This analysis reveals that while all molecules are to zeroth order correlated, that is, that they are all found in dense molecular clouds, there are three distinct groups of molecules distinguished by the location of their emission within the nuclear region. N2H+, C18O, HNC, and HCN are widespread and bright, good overall tracers of dense molecular gas. C2H and C34S, tracers of photodissociation region chemistry, originate exclusively from the central 50-100 pc region, where radiation fields are high. The third group of molecules, CH3OH and HNCO, correlates well with the expected locations of bar-induced orbital shocks. The good correlation of HNCO with the established shock tracer molecule CH3OH is evidence that this molecule, whose chemistry has been uncertain, is indeed produced by the processing of grain mantles. HC3N is observed to correlate tightly with 3 mm continuum emission, demonstrating that the young starbursts are the sites of the warmest and densest molecular gas. We compare our HNC images with the HCN images of Downes and coworkers to produce the first high-resolution, extragalactic HCN/HNC map: the HNC/HCN ratio is near unity across the nucleus, and the correlation of both of these gas tracers with star formation is excellent. The ratio exhibits no obvious correlation with gas temperature or star formation strength.
Measurement of structural changes to a food material during dehydration

Rates of dehydration/rehydration are important quality parameters for dried products. Theoretically, if there are no adverse effects on the integrity of the tissue structure, it should absorb water to the same moisture content of the initial product before drying.The purpose of this work is to semi-automate the process of detection of cell structure boundaries as a food is dehydrated and rehydrated. This will enable food materials researchers to quantify changes to material’s structure as these processes take place. Images of potato cells as they were dehydrated and rehydrated were taken using an electron microscope. Cell boundaries were detected using an image processing algorithm. Average cell area and perimeter at each stage of dehydration were calculated and plotted versus time. The results show that the algorithm can successfully identify cell boundaries.