Miracle-dz/UniFAR-FTUs huggingface dataset:
Constructing Speciication Morphisms

Speciication morphisms underlie the reenement of algebraic speciications and provide the logical foundations for algorithm and data structure design. We present four techniques for formally, even mechanically, constructing speciication morphisms. The rst two techniques, verifying a manually constructed signature morphism and composition of speciication morphisms are well-known. The remaining two techniques exploit the axioms of the source speciication to help infer the translation of sort and function symbols from the source speciication. The third, unskolemization, nds the translation of a function symbol by replacing occurrences of it in an axiom by an existentially quantiied variable. A constructive proof of the translated axiom yields a witness to the existential that serves as the desired translation of the function symbol. The fourth technique , connections between speciications, allows the transfer of structure from one spec-iication morphism to another. The unskolemization and connection techniques arose as abstractions from the algorithm design tactics implemented in the KIDS program transformation system (Smith (1990)). They suggest a more general approach to providing mechanized support for applying design knowledge expressed axiomatically.
Author ' s personal copy Learning about prospective mates in male fruit fl ies : effects of acceptance and rejection

Keywords: Drosophila melanogaster fruit fly learning mate choice sexual behaviour Neurogenetic research in fruit flies (Drosophila melanogaster) has established numerous protocols that illustrate flies' rich behavioural repertoire as well as excellent learning and memory abilities. To place that information in an evolutionary context, we followed up on earlier studies by evaluating the effect of experience with a variety of relevant female categories on males' courtship behaviour. We found, for the first time, that the experience of mating with conspecific females caused males to subsequently show lower levels of courtship towards heterospecific females compared to control males. These courtship levels, however, were higher than those of males that had experienced rejection by heterospecific females. Courtship reduction was selective: males that mated conspecifically did not subsequently show low levels of courting other conspecific females, and males that were rejected by recently mated conspecific females did not show low levels of courting heterospecific females. Interestingly, males that mated with virgin conspecifics and males that were rejected by virgin heterospecifics subsequently showed similar levels of low courtship towards recently mated conspecific females, suggesting that males find mated females unattractive after encountering virgin females. Males, however, showed higher levels of courtship towards mated females after mating with simulated mated females than after mating with control virgin females. Overall, our results indicate that adaptive use of learning by male fruit flies enhances mating success and reduces time and effort pursuing relatively less desirable or attainable females. The successful establishment of Drosophila melanogaster as a key model system for studying the neurogenetics of learning and memory (Quinn et al. 1974; Tully 1996; Keene & Waddell 2007) has led to the proliferation of ingenious protocols for quantifying learning and memory in this species (Davis 1996; Siwicki & Ladewski 2003). The advanced mechanistic work on fruit fly learning has highlighted two significant issues. First, evolutionary biologists got it wrong by underestimating learning in short-lived, small-brained insects (Mayr 1974). Second, we only have limited knowledge of the function, adaptive significance and evolutionary consequences of fruit fly learning. This is in spite of the fact that fruit flies have also served as a prominent model system in evolutionary biology and that learning can influence key evolutionary processes, including the strength and direction of sexual selection and the fate of partially diverged populations (e.g. To help fill the gaps in our knowledge of the adaptive significance of learning in fruit flies, we …
Control of a nursing bed based on a hybrid brain-computer interface

In this paper, we propose an intelligent nursing bed system which is controlled by a hybrid brain-computer interface (BCI) involving steady-state visual evoked potential (SSVEP) and P300. Specifically, the hybrid BCI includes an asynchronous brain switch based on SSVEP and P300, and a P300-based BCI. The brain switch is used to turn on/off the control system of the electric nursing bed through idle/control state detection, whereas the P300-based BCI is for operating the nursing bed. At the beginning, the user may focus on one group of flashing buttons in the graphic user interface (GUI) of the brain switch, which can simultaneously evoke SSVEP and P300, to switch on the control system. Here, the combination of SSVEP and P300 is used for improving the performance of the brain switch. Next, the user can control the nursing bed using the P300-based BCI. The GUI of the P300-based BCI includes 10 flashing buttons, which correspond to 10 functional operations, namely, left-side up, left-side down, back up, back down, bedpan open, bedpan close, legs up, legs down, right-side up, and right-side down. For instance, he/she can focus on the flashing button “back up” in the GUI of the P300-based BCI to activate the corresponding control such that the nursing bed is adjusted up. Eight healthy subjects participated in our experiment, and obtained an average accuracy of 93.75% and an average false positive rate (FPR) of 0.15 event/min. The effectiveness of our system was thus demonstrated.
Learning Lexical Embeddings with Syntactic and Lexicographic Knowledge

We propose two improvements on lexical association used in embedding learning: factorizing individual dependency relations and using lexicographic knowledge from monolingual dictionaries. Both proposals provide low-entropy lexical cooccurrence information, and are empirically shown to improve embedding learning by performing notably better than several popular embedding models in similarity tasks. 1 Lexical Embeddings and Relatedness Lexical embeddings are essentially real-valued distributed representations of words. As a vectorspace model, an embedding model approximates semantic relatedness with the Euclidean distance between embeddings, the result of which helps better estimate the real lexical distribution in various NLP tasks. In recent years, researchers have developed efficient and effective algorithms for learning embeddings (Mikolov et al., 2013a; Pennington et al., 2014) and extended model applications from language modelling to various areas in NLP including lexical semantics (Mikolov et al., 2013b) and parsing (Bansal et al., 2014). To approximate semantic relatedness with geometric distance, objective functions are usually chosen to correlate positively with the Euclidean similarity between the embeddings of related words. Maximizing such an objective function is then equivalent to adjusting the embeddings so that those of the related words will be geometrically closer. The definition of relatedness among words can have a profound influence on the quality of the resulting embedding models. In most existing studies, relatedness is defined by co-occurrence within a window frame sliding over texts. Although supported by the distributional hypothesis (Harris, 1954), this definition suffers from two major limitations. Firstly, the window frame size is usually rather small (for efficiency and sparsity considerations), which increases the false negative rate by missing long-distance dependencies. Secondly, a window frame can (and often does) span across different constituents in a sentence, resulting in an increased false positive rate by associating unrelated words. The problem is worsened as the size of the window increases since each false-positive n-gram will appear in two subsuming false-positive (n+1)-grams. Several existing studies have addressed these limitations of window-based contexts. Nonetheless, we hypothesize that lexical embedding learning can further benefit from (1) factorizing syntactic relations into individual relations for structured syntactic information and (2) defining relatedness using lexicographic knowledge. We will show that implementation of these ideas brings notable improvement in lexical similarity tasks.
Reliable Information Transmission: A Chaotic Sequence-Based Authentication Scheme for Radio Environment Maps Enabled Cognitive Radio Networks

With the intent of efficient occupying under-utilized spectrum, radio environment map (REM) based cognitive radio (CR) networking is proposed to facilitate the distributed spectrum sensing. Although the operational aspects of REM-enabled CR network are being studied actively, its security aspects have attracted very little attention. In this paper, we identify the security threats and propose generally distributed authentication architecture for REM-enabled CR networks. Furthermore, an adaptive authentication protocol (AAP) is presented. Employing channel encoding techniques and chaos sequence, authentication data is embedded into channel data as random noise. The error of host data caused by secret data can be corrected via error correcting encoding technique. The receiver can then use the secret information extracted from channel data to authenticate if the received data is sent by the user claimed. To the best of our knowledge, that is the first attempt to provide authentication mechanism for REM-enabled CR network.
Toward the Automatic Assessment of Behavioral Distrubances of Dementia

Advances in healthcare have dramatically increased life expectancy in the United States over the course of the last century. The challenges of caring for a graying population are exemplified by Alzheimer‘s disease (AD), the most common cause of dementia among persons age 65 and older. The current annual direct and indirect cost of 100 billion dollars devoted to dementia care will increase as the number of Americans suffering from AD nearly triples to 14 million by the year 2050 [6]. Approximately 90% of individuals with dementia exhibit one or more behavioral disturbances over the course of the illness [3]. These behaviors can be broadly classified as physically aggressive, physically non-aggressive (e.g., wandering), verbally aggressive, and verbally non-aggressive (i.e., repetitive vocalizations). These symptoms not only reduce the quality of life of the individual with dementia and his/her caregiver, but also lead to premature institutionalization, inappropriate and excessive physical and chemical restraints and attendant medical consequences such as falls. The psychosocial care of the nursing home resident is affected by inadequacies in staffing and training that are ubiquitous. As a result, clinical data often consists of brief observations of residents over relatively short periods of time, filtered through the lens of an overburdened staff member. In the absence of objective, reliable assessment and outcomes measurement methodologies, effectiveness of behavioral and pharmacological interventions cannot be determined. Pervasive technology holds the promise of developing objective, real-time, continuous assessment and outcomes measurement methodologies that were previously unfeasible. Such technologies can contribute greatly to a deeper understanding of the activity and behavior patterns of individual residents, and the physical, environmental and psychosocial correlates of these patterns. These kinds of applications accord very well with research goals articulated by the International Psychogeriatric Association in 2002 [1].
REFWA: An Efficient and Fair Congestion Control Scheme for LEO Satellite Networks

This paper examines some issues that affect the efficiency and fairness of the Transmission Control Protocol (TCP), the backbone of Internet protocol communication, in multi-hops satellite network systems. It proposes a scheme that allows satellite systems to automatically adapt to any change in the number of active TCP flows due to handover occurrence, the free buffer size, and the bandwidth-delay product of the network. The proposed scheme has two major design goals: increasing the system efficiency, and improving its fairness. The system efficiency is controlled by matching the aggregate traffic rate to the sum of the link capacity and total buffer size. On the other hand, the system min-max fairness is achieved by allocating bandwidth among individual flows in proportion with their RTTs. The proposed scheme is dubbed Recursive, Explicit, and Fair Window Adjustment (REFWA). Simulation results elucidate that the REFWA scheme substantially improves the system fairness, reduces the number of packet drops, and makes better utilization of the bottleneck link. The results demonstrate also that the proposed scheme works properly in more complicated environments where connections traverse multiple bottlenecks and the available bandwidth may change over data transmission time
QOS mapping for Fine Granular Scalability with base layer scaling

Scalable video coding is receiving increasing attention. However, few papers address QoS mapping with regard to scalable video coding. This paper uses Fine Granular Scalability with base layer scaling that offers application-level QoS control. An experiment is conducted that uses the DSIS method to subjectively assess Fine Granular Scalability. The results show that the maximum of the mean grading point fell as the base-layer Size value decreased. Our results also show that Fine Granular Scalability provides only SNR scalability, not subjective image quality scalability. A multiple regression analysis shows that we can establish QoS mapping between user and application-levels by using both application-level QoS parameters and a feasible human factor. Furthermore, we show that FGS can adjust to not only a wide range of channel capacities but also a wide variety of users by using the indicated QoS mapping.
Energy-efficient multi-hop transmission for machine-to-machine communications

Emerging machine-to-machine communication scenarios are envisioned to deal with more stringent quality-of-service demands. This relates mainly to outage and latency requirements, which are for example for safety-critical messages quite different than for traditional applications. On the other hand, it is widely accepted that machine-to-machine communication systems need to be energy-efficient because of the widespread use of battery-powered devices, but also due to their huge deployment numbers. In this paper, we address these issues with respect to multi-hop transmissions. Specifically, we deal with minimizing the consumed energy of transmitting a packet with end-to-end outage and latency requirements. We account for the cases in which the system can utilize solely average channel state information, or in addition obtain and profit from instantaneous channel state information. The developed solution is based on convex optimization. It is shown numerically that despite accounting for the energy consumption of acquiring instantaneous channel state information, especially as the outage and latency requirements become tough, it is by up to 100 times more energy efficient to convey a packet with instantaneous than with average channel state information.
Regional blood flow during cardiopulmonary resuscitation in dogs

To determine differences in regional blood flow during CPR versus normal cardiac function, the authors measured regional blood flow to several organs in 19 pentobarbital-anesthetized dogs (6–12 kg). Regional blood flow was measured during sinus rhythm in five dogs and during electrically induced ventricular fibrillation with CPR in the other 14 dogs. Regional blood flow and cardiac output were measured using radioactively labeled polystyrene microspheres of 15 ± 3 μ diameter, injected into the left ventricle. Adequacy of microsphere mixing at low cardiac outputs was verified by comparing flow rates to paired organs. Cardiac output was 175 ml/kgμmin during sinus rhythm versus 47 ml/kgμmin during CPR. Flow to all organs sampled was less during CPR, but the relative decrease varied widely. The ratios of regional blood flow during CPR to regional blood flow during sinus rhythm were 90% for brain, 35% for heart, 15% for kidneys, 17% for adrenal glands, 14% for pancreas, 3% for spleen, and 33% for small intestine. These results provide baseline values for regional blood flow during CPR which can be used to evaluate alternative CPR techniques and/or drugs which may improve perfusion of vital organs during CPR.
Premises of an algebra of Japanese characters

The Japanese language is made mostly of three characters sets: hiragana, katakana and kanji characters. Kanji characters are inherited from Chinese, and include thousands of glyphs. Characters, especially kanji, memorisation is thus an extremely challenging task for learners of the Japanese language, and even for native speakers who tend to forget the meaning or writing of uncommon characters. In this paper, we address this problem by proposing a novel memorisation technique based on an algebra defined for these kanji characters. By reusing classic algebra notations, the learner is able to rely on acquired knowledge (numbers algebra) to support his/her memorisation of Japanese characters. In addition, we consider automatic processing and application of this algebra to low-spec systems, for instance embedded systems.
Low-power photon upconversion through triplet–triplet annihilation in polymers

Low-power upconversion via sensitized triplet–triplet annihilation (TTA-UC) is a useful and versatile process that allows for the conversion of optical radiation into photons of higher energy. While this effect had been known to occur in solution for some 50 years, it was only very recently realized for the first time in polymers. The possibility to realize the TTA-UC process in solid materials is important for a variety of applications that range from the optimization of photovoltaic devices to bioimaging. This article provides a brief introduction to the field, summarizes the underlying photophysical aspects, reviews the design concepts for TTA-UC in polymers, and summarizes the recent advances in the development of such materials.
Formal verification in a component-based reuse methodology

There is an important trend towards design processes based on the reuse of predesigned components. We propose a formal verification approach which smoothly integrates with a component based system-level design methodology. Once a timed Petri net model corresponding to the interface logic has been produced the correctness of the system can be formally verified. The verification is based on the interface properties of the connected components and on abstract models of their functionality, without assuming any knowledge regarding their implementation. We have both developed the theoretical framework underlying the methodology and implemented an experimental environment using model checking techniques.
Solidification and Particle Entrapment during Continuous Casting of Steel

Avoiding particle entrapment into the solidifying shell of a steel continuous caster is important to improve the quality of the continuous cast product. Therefore, the fluid flow dynamics in the steel melt and mushy zone, heat transfer and solidification of the steel shell, as well as the motion and entrapment of inclusion particles during the casting process were investigated using computational models. Solidification of the strand shell is modelled with an enthalpy‐formulation by assuming a columnar morphology in the mushy zone. The motion of particles is tracked with a Lagrangian approach. When the particles reach the solidification front, they can be entrapped/engulfed into the solid shell or pushed away from the solidification front, depending on the mushy zone morphology and the forces acting on them. The current paper focuses on the mould region at a steel continuous caster, including the submerged entry nozzle (SEN) and 1.2 m length of the strand. The results are validated with plant measurements and demonstrate the potential of the model to predict fluid flow, shell growth and the positions and the amount of entrapped/engulfed particles in the solidifying strand.
Polyethylene Glycol Protects Injured Neuronal Mitochondria

Objective: Polyethylene glycol (PEG), a hydrophilic polymer, can immediately repair neuronal membranes and inhibit free radical production following trauma. The aim of this study is to examine whether PEG can directly repair mitochondria in the event of trauma. Method: Purified brain mitochondria from guinea pigs were used. Mitochondrial function was assessed by biochemical methods and structural changes were observed by both fluorescence light microscopy and coherent anti-Stokes Raman scattering microscopy. Results: We present evidence suggesting that PEG is capable of directly reducing injury to mitochondria independent of plasma membrane repair. Specifically, the suppression of oxygen consumption rate of purified mitochondria due to H2O2 and/or calcium can be significantly reversed by 12.5 mM PEG. PEG also significantly reduced mitochondrial swelling due to similar injury. Furthermore, we have shown that such PEG-mediated mitochondrial protection is dependent on the molecular weight of PEG, suggesting a direct physical blockade of mitochondrial permeability transitional pore by PEG. Conclusion: These findings, coupled with previous evidence that PEG enters the cytosol following mechanical trauma, strongly indicate that there are at least 2 avenues of PEG-mediated cytoprotection in mechanically injured spinal cords: repair of plasma membrane and protection of mitochondria.
Dfm1 Forms Distinct Complexes with Cdc48 and the ER Ubiquitin Ligases and Is Required for ERAD

Proteins imported into the endoplasmic reticulum (ER) are scanned for their folding status. Those that do not reach their native conformation are degraded via the ubiquitin‐proteasome system. This process is called ER‐associated degradation (ERAD). Der1 is known to be one of the components required for efficient degradation of soluble ERAD substrates like CPY* (mutated carboxypeptidase yscY). A homologue of Der1 exists, named Dfm1. No function of Dfm1 has been discovered, although a C‐terminally hemagglutinin (HA)3‐tagged Dfm1 protein has been shown to interact with the ERAD machinery. In our studies, we found Dfm1‐HA3 to be an ERAD substrate and therefore not suitable for functional studies of Dfm1 in ERAD. We found cellular, non‐tagged Dfm1 to be a stable protein. We identified Dfm1 to be part of complexes which contain the ERAD‐L ligase Hrd1/Der3 and Der1 as well as the ERAD‐C ligase Doa10. In addition, ERAD of Ste6*‐HA3 was strongly dependent on Dfm1. Interestingly, Dfm1 forms a complex with the AAA‐ATPase Cdc48 in a strain lacking the Cdc48 membrane‐recruiting component Ubx2. This complex does not contain the ubiquitin ligases Hrd1/Der3 and Doa10. The existence of such a complex might point to an additional function of Dfm1 independent from ERAD.