Miracle-dz/UniFAR-FTUs huggingface dataset:
Algorithms for Phylogenetic Tree Reconstruction

Scientists often wish to use the information contained in the DNA sequences of a collection of organisms, or taxa, to infer the evolutionary relationships among those taxa. These evolutionary relationships are generally represented by a labeled binary tree, called a phylogenetic tree. The phylogeny reconstruction problem is computationally di cult because the number of possible solutions increases rapidly with the number of taxa to be included in the tree. For example, for 30 taxa (a moderate number of taxa given the wide availability of DNA sequence data today! ), there are 8:69 10 possible unrooted bifurcating trees to be considered. Thus, scientists are faced with the task of choosing from among a large number of trees that tree(s) which gives the "best" representation of the evolutionary relationships among the taxa based on the data. Often, optimality criteria are applied to allow trees to be compared with one another. In this case, the phylogenetic tree reconstruction problem becomes that of nding the particular tree(s) that optimize the criteria. Exhaustive search of the space of phylogenetic trees is generally not possible for more than 11 taxa, and so algorithms for e ciently searching the space of trees must be developed. Branch-and-bound methods can reasonably be applied for up to about 20 taxa, but no computationally e cient exact algorithms have been developed for problems larger than this. Therefore, scientists generally rely on heuristic algorithms, such as stepwise-addition and star decomposition methods. However, such algorithms generally involve a prohibitive amount of computation time for large problems and often nd trees that are only locally optimal. Recently, stochastic search algorithms, such as simulated annealing, genetic algorithms, and Markov chain Monte Carlo (MCMC) methods, have been developed and successfully applied to phylogenetic problems. We discuss and compare some of the methods available for phylogenetic tree reconstruction under an optimality criteria, and suggest some directions for future
TASK-3 Knockout Mice Exhibit Exaggerated Nocturnal Activity, Impairments in Cognitive Functions, and Reduced Sensitivity to Inhalation Anesthetics

The TASK-3 channel is an acid-sensitive two-pore-domain K+ channel, widely expressed in the brain and probably involved in regulating numerous neuronal populations. Here, we characterized the behavioral and pharmacological phenotypes of TASK-3 knockout (KO) mice. Circadian locomotor activity measurements revealed that the nocturnal activity of the TASK-3 KO mice was increased by 38% (P < 0.01) compared with wild-type littermate controls, light phase activity being similar. Although TASK-3 channels are abundant in cerebellar granule cells, the KO mice performed as well as the wild-type mice in walking on a rotating rod or along a 1.2-cm-diameter beam. However, they fell more frequently from a narrower 0.8-cm beam. The KO mice showed impaired working memory in the spontaneous alternation task, with the alternation percentage being 62 ± 3% for the wild-type mice and 48 ± 4% (P < 0.05) for the KO mice. Likewise, during training for the Morris water-maze spatial memory task, the KO mice were slower to find the hidden platform, and in the probe trial, the female KO mice visited fewer times the platform quadrant than the male KO and wild-type mice. In pharmacological tests, the TASK-3 KO mice showed reduced sensitivity to the inhalation anesthetic halothane and the cannabinoid receptor agonist WIN55212-2 mesylate [(R)-(+)-[2,3-dihydro-5-methyl-3-(4-morpholinylmethyl)pyrrolo[1,2,3-de]-1,4-benzoxazin-6-yl]-1-naphthalenylmethanone mesylate] but unaltered responses to the α2 adrenoceptor agonist dexmedetomidine, the i.v. anesthetic propofol, the opioid receptor agonist morphine, and the local anesthetic lidocaine. Overall, our results suggest important contributions of TASK-3 channels in the neuronal circuits regulating circadian rhythms, cognitive functions, and mediating specific pharmacological effects.
Offline handwritten Jawi recognition using the trace transform

The Trace transform, a generalization of the Radon transform, allows one to construct image features that are invariant to a chosen group of image transformations. In this paper, we use features that are known as object signatures, which are invariant to affine distortion, generated by the trace transform to discriminate between offline handwritten Jawi sub words. The process consists of tracing an image with straight lines, along which certain functionals of the image function are calculated, in all possible orientations. For each combination of functionals we derive the object signature which is a function of orientation of the tracing lines. In this paper, we demonstrate the usefulness of the derived signature and compare the result of the recognition with those obtained by using features based on affine moment invariants and angular radial transforms.
From functional to object-oriented programming: a smooth transition for beginners

Many Computer Science curricula at universities start programming with a functional programming language (for instance, SML, Haskell, Scheme) and later change to the imperative programming paradigm. For the latter usually the object-oriented programming language Java is used. However, this puts a burden on the students, since even the smallest Java program cannot be formulated without the notion of class and static and public method. In this paper we present an approach for changing from functional to object-oriented programming. Using (Standard) ML for the functional programming paradigm, it still prepares the decisive notions of object-orientation by specific constructs of this language. As experience at the University of Kiel has shown, this smoothes the transition and helps the students getting started with programming in the Java language.
Efficient annotation of image data sets for computer vision applications

High quality ground truth data sets are crucial for the development of image recognition systems. However, the task of annotating large image data sets manually takes a lot of time and effort. In order to lower the burden for the development of application-specific image recognition systems, we developed an advanced user interface. This interface is especially designed for non-expert users with little-to-no knowledge of computer vision techniques. The interface presents images clustered by similarity and allows for an efficient and simple annotation of large data sets. The integration of overview+detail concepts allows the precise navigation inside large data sets. The interface can be used without prior instructions on the underlying concepts, like self-organizing maps, image features or visualization techniques.
Dispersion, coordination and performance in global software teams: A systematic review

Effective team coordination is crucial for successful global software projects. Although considerable research effort has been made in this area, no agreement has been reached on the influence of dispersion on team coordination and performance. The objective of this paper is to summarize the evidence on the relationship among context dispersion, team coordination and performance in global software projects. We have performed a Systematic literature review (SLR) to collect relevant studies and a thematic analysis to synthesize the extracted data. We found 28 primary studies reporting the impact of five dispersion dimensions on team performance. Previously, only two primary studies considered and distinguished all of these dispersion dimensions in studying dispersed team performance. The dispersion dimensions affect team outcomes indirectly through influencing organic and mechanistic coordination processes. Empirical evidence show that geographical dispersion impacts negatively and temporal dispersion has a mixed effect on team performance. While studies with teams working across different time zones shows a tendency that the team performance is pessimistically perceived, studies that use direct measure on task performance shows a positive association to temporal dispersion. The paper provides implications for future research and practitioners in establishing effective distributed team coordination.
Frequency offset correction in single sideband (SSB) speech by deep neural network for speaker verification

Communication system mismatch represents a major influence for loss in speaker recognition performance. This paper considers a type of nonlinear communication system mismatch- modulation/demodulation (Mod/DeMod) carrier drift in single sideband (SSB) speech signals. We focus on the problem of estimating frequency offset in SSB speech in order to improve speaker verification performance of the drifted speech. Based on a two-step framework from previous work, we propose using a multi-layered neural network architecture, stacked denoising autoencoder (SDA), to determine the unique interval of the offset value in the first step. Experimental results demonstrate that the SDA based system can produce up to a +16.1% relative improvement in frequency offset estimation accuracy. A speaker verification evaluation shows a +65.9% relative improvement in EER when SSB speech signal is compensated with the frequency offset value estimated by the proposed method. Index Terms: frequency offset, single sideband, speaker verification, denoising autoencoder
Remarkably Distinct Gene Expression Patterns Estrogen Receptor Status in Breast Cancer Is Associated with Updated

To investigate the phenotype associated with estrogen receptor (ER) expression in breast carcinoma, gene expression profiles of 58 nodenegative breast carcinomas discordant for ER status were determined using DNA microarray technology. Using artificial neural networks as well as standard hierarchical clustering techniques, the tumors could be classified according to ER status, and a list of genes which discriminate tumors according to ER status was generated. The artificial neural networks could accurately predict ER status even when excluding top discriminator genes, including ER itself. By reference to the serial analysis of gene expression database, we found that only a small proportion of the 100 most important ER discriminator genes were also regulated by estradiol in MCF-7 cells. The results provide evidence that ER and ER tumors display remarkably different gene-expression phenotypes not solely explained by differences in estrogen responsiveness.
Wireless Mesh Network for Emergency Response System Based on Embedded System

In public places such as banks, hospitals and schools which require higher safety, when the emergent circumstances of serious natural disasters or terrorist attacks are happened, the traditional means of communication rely on the base station were often restricted seriously by the environment and lots of difficulties are created to the rescue work. To counter this limitation, an emergency response system based on wireless mesh network for public safety defense is proposed in this paper. ARM (Advanced RISC Machines) was used as the kernel control unit of this system. The system network structure is established, the hardware architecture of the system is designed, and the system working procedures is given. The characteristic of the system is self-organization, without-center and the unnecessary for base stations. The system can be used in many emergent occasions rescuing at the scene and play a unique role in the emergency system of the community.
Traveling-wave microwave fiber-optic links

A traveling-wave microwave fiber-optic link (TW MFL) is proposed and demonstrated for the first time. The structure is electrically equivalent to a traveling-wave microwave amplifier in which the transistors are replaced by individual optical fiber link elements using laser diode (LD)-photodiode (PD) pairs. This results in two transmission-line structures that are periodically loaded with LDs and PDs, respectively, and connected to one another by a fiber array. A three-element TW MFL has been constructed using commercially available components to demonstrate the concept. Over the design bandwidth of 200 MHz-2 GHz, the input and output return loss is better than approximately 10 dB each, while the link gain of -20 dB is in agreement with simulation results. The link gain is seen to increase as the number of link elements is increased. Measured S-parameter results also show the deleterious impact of terminating impedance mismatches and optical delay detuning on the TW MFL's frequency response.
Managing evolution in software product lines: a model-checking perspective

In Software Product Line (SPL) engineering, similar software products are developed in families rather than individually. Developing similar software at once leads to new challenges. In particular, the model checking problem for SPL is harder because it has to deal with potentially many products and identify exactly which ones do not work properly. In previous work, we introduced Featured Transition Systems as a compact behavioural model for SPL. We also proposed new algorithms that model check all the products of the SPL efficiently, by taking into account the commonality between them to reduce the verification time. However, our current approach does not consider that SPL can evolve. If a new feature is added to the SPL, previous verification results cannot be reused. In this paper, we define formally two particular classes of features. Using simulation relations, we show that we may anticipate the properties of some products introduced by those features. We discuss interesting perspectives and present the challenges that are still ahead.
Foreign Portfolio Investment, Foreign Bank Lending, and Economic Growth

In contrast to the empirical literature's focus on foreign direct investment (FDI), this study examines the effects of foreign portfolio investment (FPI) and "other" foreign investment (OFI) on economic growth using data on 88 countries from 1977 through 2000. Most measures suggest that FPI has no effect, and some results indicate that OFI has a negative impact on growth that is somewhat mitigated by initial financial and/or legal development. However, these results are questionable due to possible simultaneity bias. The empirical analyses also examine whether non-FDI foreign investment affects growth indirectly. FPI does not correlate positively with macroeconomic volatility, but the results indicate that the negative indirect effect of OFI through macroeconomic volatility comprises a substantial portion of the gross negative effect of OFI on growth.
Ontology change: classification and survey

Abstract Ontologies play a key role in the advent of the Semantic Web. An important problem when dealing with ontologies is the modification of an existing ontology in response to a certain need for change. This problem is a complex and multifaceted one, because it can take several different forms and includes several related subproblems, like heterogeneity resolution or keeping track of ontology versions. As a result, it is being addressed by several different, but closely related and often overlapping research disciplines. Unfortunately, the boundaries of each such discipline are not clear, as the same term is often used with different meanings in the relevant literature, creating a certain amount of confusion. The purpose of this paper is to identify the exact relationships between these research areas and to determine the boundaries of each field, by performing a broad review of the relevant literature.
Lost for Words or Loss of Memories? Autobiographical Memory in Semantic Dementia

Recent reports have suggested that patients with semantic dementia show a loss of early (remote) auto‐biographical memories with pronounced sparing of recent memories (Graham & Hodges, 1997; Snowden, Griffiths, & Neary, 1996), i.e., a ‘reversed’ temporal gradient or ‘Ribot effect’. At first sight, these findings suggest that the deficits in ‘semantic’ dementia go beyond the semantic domain, involving aspects of autobiographical (episodic) memory. It has also been proposed that there is a ‘step‐like’ function with personal memories preserved for 18 months to 2 years in the immediate past. This view is consistent with the theory that the hippocampal complex/medial temporal lobe (relatively intact in semantic dementia) plays a time‐limited role in the acquisition and storage of memories, while the temporal neocortex (damaged in semantic dementia) is required for long‐term storage and retrieval. In this study we ask whether (a) previous tests have underestimated the integrity of remote memory in semantic dementia as a result of not allowing for these patients' comprehension and language production difficulties, and (b) whether a recency effect, if obtained, is genuinely step‐like or more graded. We used a cued autobiographical memory interview with semantic dementia patient, IH, to examine the effect of providing increasingly specific lexical cues to probe salient events throughout his lifespan. Results demonstrated that the provision of specific cues enabled IH to access and express memories from his childhood and early adulthood as well as from more recent times. There was a gentle recency effect only for intermediate levels of cueing, indicating that recent memories were easier to retrieve and/or express in the absence of specific cues, but this effect was graded, with no evidence of a step‐like cut‐off at 18 months or 2 years before testing. In brief, our findings are consistent with the view that the deficits in semantic dementia are predominantly or exclusively semantic, rather than involving the storage of autobiographical memories per se.
The adjuvant use of calcium fructoborate and borax with etanercept in patients with rheumatoid arthritis: Pilot study

Objective: This study was designed to evaluate the effects calcium fructoborate (CFB) and sodium tetraborate (NTB) as supplements in Iraqi patients with active rheumatoid arthritis (RA) maintained on etanercept. Materials and Methods: A double-blind randomized placebo-controlled clinical trial with 60 days treatment period was carried out at Baghdad Teaching Hospital, Medical city, Baghdad, Iraq. Eighty RA patients were randomized into three groups to receive either 220 mg/day CFB, 55 mg/day NTB in capsule dosage form (equivalent to 6 mg elemental Boron), or placebo formula once daily. Only 72 patients completed the study. All patients were clinically evaluated utilizing DAS28-erythrocyte sedimentation rate (ESR), simple disease activity index-C-reactive protein (CRP), and clinical disease activity index scores at baseline, and at the end of the study. Venous blood was obtained at baseline and after 60 days, and utilized for the measurement of ESR, hemoglobin, in addition to evaluation of high-sensitivity CRP (hsCRP), tumor necrosis factor-α (TNF-α), interleukin-1α (IL-1α) and IL-6. Results: After 60 days, both types of boron significantly improve the clinical scores, in association with significant decrease in the serum levels of ESR, hsCRP, IL-1α, IL-6, and TNF-α with remarkable superiority for calcium fructoborate (CFB) over sodium tetraborate (NTB), compared to baseline and placebo-treated group. Conclusion: The use of boron, as adjuvant with etanercept, has potentiated therapeutic outcomes in RA patients, and may be a new strategy to improve treatment, and avoid the problems associated with biologics utilized in RA treatment.
A generic approach to classify sports video shots and its application in event detection

Shot type is useful information for semantic sports video analysis. Most existing approaches utilize predefined rules and domain knowledge to derive shot types in sports video. Although these methods have achieved promising results in some specific games, it is hard to extend them from one sport to another. To address this problem, we propose a generic approach to classify shots in sports video. Our approach utilizes bag of visual words model to represent key frame for each shot based on Scale Invariant Feature Transform (SIFT) feature points; either Support Vector Machine (SVM) or Probabilistic Latent Semantic Analysis (PLSA) are then employed to classify key frame to determine shot type. As our approach relies little on domain knowledge, it can be more easily extended to different sports. We have evaluated our shot classification approach over five types of sports video and have achieved promising results. To show the usefulness and effectiveness of our shot classification, we apply the results of shot type to detect events in basketball video via a generative-discriminative model. In addition, we have observed that some common visual parts frequently appear across various shots in the same sport or even different but relevant sports. For instance, soccer and basketball are relevant sports in the sense of field-ball game. Motivated by this observation, we attempt to alleviate the problem of insufficient sports video data in some applications by sharing these visual parts across different but relevant kinds of sports.
Performance analysis of DS-OCDMA using novel multi-level periodic codes

In this paper we present a theoretical simulation that evaluate the performance of direct-sequence optical code-division multiple-access (DS-OCDMA) system, using a novel periodic optical encoder applied to fiber-to-the-X (FTTX) passive optical network (PONs). We investigate the performances in terms of signal to noise ratio (SNR) and bit error rate (BER) in the presence of multiple access interference (MAI) and an additive white Gaussian noise (AWGN). Three groups of parameters were considered in this work: the number of users, the parameters related to the encoder and the parameters of the receiver.
Recurrent Deep Stacking Networks for Speech Recognition.

This paper presented our work on applying Recurrent Deep Stacking Networks (RDSNs) to Robust Automatic Speech Recognition (ASR) tasks. In the paper, we also proposed a more efficient yet comparable substitute to RDSN, Bi- Pass Stacking Network (BPSN). The main idea of these two models is to add phoneme-level information into acoustic models, transforming an acoustic model to the combination of an acoustic model and a phoneme-level N-gram model. Experiments showed that RDSN and BPsn can substantially improve the performances over conventional DNNs.