Miracle-dz/UniFAR-FTUs huggingface dataset:
Modelling Language Acquisition : Lexical Grounding Through Perceptual Features

A neural network model of language acquisition is introduced, motivated by current research in psychology and linguistics. It uses both extra-linguistic perceptual features and symbolic representations of words. The network learns to auto-associate these inputs to their linguistic labels, as well as to predict the next word in the corpus. This is interpreted to model both the acquisition of a lexicon, and the beginnings of syntax or grammar (word order). Furthermore, the inclusion of the extralinguistic perceptual features is argued to be a form of direct developmental grounding in embodied concepts, which will allow the later learning of more abstract concepts to be grounded indirectly in meaning through relations to the first words. Through this bootstrapping process, future versions of the network may be scalable to large vocabularies, and may bridge the gap between high-dimensional and embodied theories of meaning.
Analyzing Activity Behavior and Movement in a Naturalistic Environment Using Smart Home Techniques

One of the many services that intelligent systems can provide is the ability to analyze the impact of different medical conditions on daily behavior. In this study, we use smart home and wearable sensors to collect data, while (n = 84) older adults perform complex activities of daily living. We analyze the data using machine learning techniques and reveal that differences between healthy older adults and adults with Parkinson disease not only exist in their activity patterns, but that these differences can be automatically recognized. Our machine learning classifiers reach an accuracy of 0.97 with an area under the ROC curve value of 0.97 in distinguishing these groups. Our permutation-based testing confirms that the sensor-based differences between these groups are statistically significant.
Growth factors influence contractility and alpha-smooth muscle actin expression in bovine lens epithelial cells.

PURPOSE To determine whether basic fibroblast growth factor (bFGF) and transforming growth factor-beta 2 (TGF-beta 2) influence the contractile activity and the expression of alpha-smooth muscle actin (alpha-SMA) in bovine lens epithelial cells (LECs). To examine whether modulation of contractile activity by these growth factors depends on changes of alpha-SMA expression. METHODS Bovine LECs were cultured in collagen gel in MED 5 medium (F-12 nutrient mixture supplemented with 5% fetal bovine serum) with or without bFGF (1 to 100 ng/ml) or TGF-beta 2 (0.01 to 10 ng/ml). To evaluate collagen gel contraction, the longest and shortest diameters of the gels were measured daily for 7 days, and the area was determined. Detection of alpha-SMA in the gels was performed immunohistochemically using a mouse monoclonal antibody against alpha-SMA. The percentage of alpha-SMA-positive cells to the total number of cells was determined. RESULTS Control gels cultured with MED 5 medium alone contracted to 15.8% +/- 3.4% of their original area after 7 days. TGF-beta 2 significantly increased this contraction in a dose-dependent manner, whereas bFGF significantly decreased it. Approximately 30% of cells in the control gels were alpha-SMA positive. TGF-beta 2 significantly increased the alpha-SMA positivity dose dependently, whereas bFGF significantly decreased it. The percent positivity for alpha-SMA and the gel area showed a significant negative correlation. CONCLUSIONS TGF-beta 2 increased collagen gel contraction and alpha-SMA expression in bovine LECs, whereas bFGF decreased these parameters. Because collagen gel contraction was correlated with alpha-SMA expression, the modulation of LEC contractile activity by growth factors may be related to an effect on alpha-SMA.
The Proteolytic Processing of Seed Storage Proteins in Arabidopsis Embryo Cells Starts in the Multivesicular Bodies[W]

We have investigated the transport of storage proteins, their processing proteases, and the Vacuolar Sorting Receptor-1/Epidermal Growth Factor Receptor–Like Protein1 (VSR-1/ATELP1) receptor during the formation of protein storage vacuoles in Arabidopsis thaliana embryos by means of high-pressure freezing/freeze substitution, electron tomography, immunolabeling techniques, and subcellular fractionation. The storage proteins and their processing proteases are segregated from each other within the Golgi cisternae and packaged into separate vesicles. The storage protein–containing vesicles but not the processing enzyme–containing vesicles carry the VSR-1/ATELP1 receptor. Both types of secretory vesicles appear to fuse into a type of prevacuolar multivesicular body (MVB). We have also determined that the proteolytic processing of the 2S albumins starts in the MVBs. We hypothesize that the compartmentalized processing of storage proteins in the MVBs may allow for the sequential activation of processing proteases as the MVB lumen gradually acidifies.
Predicting the Functional Effect of Amino Acid Substitutions and Indels

As next-generation sequencing projects generate massive genome-wide sequence variation data, bioinformatics tools are being developed to provide computational predictions on the functional effects of sequence variations and narrow down the search of casual variants for disease phenotypes. Different classes of sequence variations at the nucleotide level are involved in human diseases, including substitutions, insertions, deletions, frameshifts, and non-sense mutations. Frameshifts and non-sense mutations are likely to cause a negative effect on protein function. Existing prediction tools primarily focus on studying the deleterious effects of single amino acid substitutions through examining amino acid conservation at the position of interest among related sequences, an approach that is not directly applicable to insertions or deletions. Here, we introduce a versatile alignment-based score as a new metric to predict the damaging effects of variations not limited to single amino acid substitutions but also in-frame insertions, deletions, and multiple amino acid substitutions. This alignment-based score measures the change in sequence similarity of a query sequence to a protein sequence homolog before and after the introduction of an amino acid variation to the query sequence. Our results showed that the scoring scheme performs well in separating disease-associated variants (n = 21,662) from common polymorphisms (n = 37,022) for UniProt human protein variations, and also in separating deleterious variants (n = 15,179) from neutral variants (n = 17,891) for UniProt non-human protein variations. In our approach, the area under the receiver operating characteristic curve (AUC) for the human and non-human protein variation datasets is ∼0.85. We also observed that the alignment-based score correlates with the deleteriousness of a sequence variation. In summary, we have developed a new algorithm, PROVEAN (Protein Variation Effect Analyzer), which provides a generalized approach to predict the functional effects of protein sequence variations including single or multiple amino acid substitutions, and in-frame insertions and deletions. The PROVEAN tool is available online at http://provean.jcvi. org.
Efficient Spin Injection Through Exchange Coupling at Organic Semiconductor/Ferromagnet Heterojunctions

The schematic visualization of the Alq(3) molecule on the Fe substrate with the optimized geometry at lowest total energy. When the Alq(3) molecule is relaxed on the surface, only two of the wings are lying down on the Fe surface, and the third wing remains perpendicular to the surface, showing a strong hybridization occurance.
Acidosis promotes invasiveness of breast cancer cells through ROS-AKT-NF-κB pathway

It is well known that acidic microenvironment promotes tumorigenesis, however, the underlying mechanism remains largely unknown. In the present study, we show that acidosis promotes invasiveness of breast cancer cells through a series of signaling events. First, our study indicates that NF-κB is a key factor for acidosis-induced cell invasion. Acidosis activates NF-κB without affecting STAT3 activity; knockdown of NF-κB p65 abrogates the acidosis-induced invasion activity. Next, we show that the activation of NF-κB is mediated through phosphorylation and degradation of IκBα; and phosphorylation and nuclear translocation of p65. Upstream to NF-κB signaling, AKT is activated under acidic conditions. Moreover, acidosis induces generation of reactive oxygen species (ROS) which can be suppressed by ROS scavengers, reversing the acidosis-induced activation of AKT and NF-κB, and invasiveness. As a negative regulator of AKT, PTEN is oxidized and inactivated by the acidosis-induced ROS. Finally, inhibition of NADPH oxidase (NOX) suppresses acidosis-induced ROS production, suggesting involvement of NOX in acidosis-induced signaling cascade. Of considerable interest, acidosis-induced ROS production and activation of AKT and NF-κB can be only detected in cancer cells, but not in non-malignant cells. Together, these results demonstrate a cancer specific acidosis-induced signaling cascade in breast cancer cells, leading to cell invasion.
Focal Segmental Glomerulosclerosis

Focal segmental glomerulosclerosis (FSGS) as the name implies is a histopathological pattern of lesions, where the “focal” refers to, involving minority of glomeruli and the “segmental” refers to, involving a portion of the glomerular capillary tuft caused by injury to podocytes (Fig 1A). Clinically it manifests proteinuria which can progress to nephrotic syndrome and eventually to end stage renal failure.
Reducing branch costs via branch alignment

Several researchers have proposed algorithms for basic block reordering. We call these branch alignment algorithms. The primary emphasis of these algorithms has been on improving instruction cache locality, and the few studies concerned with branch prediction reported small or minimal improvements. As wide-issue architectures become increasingly popular the importance of reducing branch costs will increase, and branch alignment is one mechanism which can effectively reduce these costs. In this paper, we propose an improved branch alignment algorithm that takes into consideration the architectural cost model and the branch prediction architecture when performing the basic block reordering. We show that branch alignment algorithms can improve a broad range of static and dynamic branch prediction architectures. We also show that a program performance can be improved by approximately 5% even when using recently proposed, highly accurate branch prediction architectures. The programs are compiled by any existing compiler and then transformed via binary transformations. When implementing these algorithms on a Alpha AXP 21604 up to a 16% reduction in total execution time is achieved.
Optimal partial feedback design for MIMO block fading channels with causal noiseless feedback

In this paper, we focus on investigating the optimal MIMO transmission strategy for forward channel capacity and forward error exponent of the MIMO block fading channels when the feedback link is causal and has a capacity constraint. In this paper, we assume a forward MIMO block fading channel where the channel state information is estimated at the receiver and partially feedback to the transmitter. The feedback link is assumed to be noiseless and causal with a feedback capacity constraint in terms of maximum number of feedback bits per fading block. We show that the design of the optimum feedback scheme is identical to the design of vector quantizer (Lloyd's algorithm [S.P. Lloyd, 1982]) with a modified distortion measure. It is shown that in the general case, the optimal feedback strategy has a general form of power water-filling cascaded with beamforming matrix as well. Furthermore, we show that the SNR gain with feedback is contributed by focusing transmission power on active eigen-channel and temporal power water-filling. The former factor contributed at most log/sub 10/(n/sub T/)n/sub R/ dB SNR gain when n/sub T/ > n/sub R/ in all SNR region while the latter contribution is significant only at low SNR region. Finally, MMSE receiver could be used to achieve the optimal capacity in the general case of partial feedback.
A Comparison of Image Processing Techniques for Bird Recognition

Bird predation is one of the major concerns for fish culture in open ponds. A novel method for dispersing birds is the use of autonomous vehicles. Image recognition software can improve their efficiency. Several image processing techniques for recognition of birds have been tested. A series of morphological operations were implemented. We divided images into 3 types, Type 1, Type 2, and Type 3, based on the level of difficulty of recognizing birds. Type 1 images were clear; Type 2 images were medium clear, and Type 3 images were unclear. Local thresholding has been implemented using HSV (Hue, Saturation, and Value), GRAY, and RGB (Red, Green, and Blue) color models on all three sections of images and results were tabulated. Template matching using normal correlation and artificial neural networks (ANN) are the other methods that have been developed in this study in addition to image morphology. Template matching produced satisfactory results irrespective of the difficulty level of images, but artificial neural networks produced accuracies of 100, 60, and 50% on Type 1, Type 2, and Type 3 images, respectively. Correct classification rate can be increased by further training. Future research will focus on testing the recognition algorithms in natural or aquacultural settings on autonomous boats. Applications of such techniques to industrial, agricultural, or related areas are additional future possibilities.
Appliaction-Specific Data Cache Systems

The design supports fast access time, optimal utilization of temporal and spatial localities adaptive to given applications, and a simple dynamic fetching mechanism with different fetch sizes. Support for dynamically varying the fetch size makes the cache equally effective for general-purpose as well as multimedia applications. Simulation shows that the average memory access time of the proposed cache is equal to that of a conventional direct-mapped cache with eight times as much space. In addition, our cache achieves better performance than a 2-way or 4-way set associative cache with twice as much space.
Social Comparison as a Vicarious Source of Self-Efficacy Information.

ABSTRACT Social comparison is an important influence on, motivation, capability self-evaluations (self-efficacy), and skillful performance. In addition, social comparative information provides a standard against which students can judge their present performance level. Students may experience. an initial sense of self-efficacy in attaining a given standard; this sense may in turn enhance motivation. As students observe their progress, self-efficacy is substantiated, and thiSsubstantiation helps to sustain motivation and promote skills. Young children's social comparisons focus on practical concerns, but by the f6). ;-th grade, students regularly use social comparative information for self-evaluative purposes. Comparisons with similar others are especially informative of one's own capabilities. Research shows that, although social comparative information indicating average achievement enhances motivation, it exerts only modest effects on self-efficacy. Self-evaluations seem to be more strongly influenced by performance outcomes and educational practices such as teacher evaluations and goal setting. Preservice teachers need to realize that educational practices such as reward structures, modeling, and tutoring also can affect students' social comparisons; these effects should be taken into account when designing instructional activities. (Concluding notes indicate ways social comparison is used in the classroom and suggest effective uses of social comparison.) (Author/RH)
Fast Approximate Inference in Higher Order MRF-MAP Labeling Problems

Use of higher order clique potentials for modeling inference problems has exploded in last few years. The algorithmic schemes proposed so far do not scale well with increasing clique size, thus limiting their use to cliques of size at most 4 in practice. Generic Cuts (GC) of Arora et al. [9] shows that when potentials are submodular, inference problems can be solved optimally in polynomial time for fixed size cliques. In this paper we report an algorithm called Approximate Cuts (AC) which uses a generalization of the gadget of GC and provides an approximate solution to inference in 2-label MRF-MAP problems with cliques of size k ≥ 2. The algorithm gives optimal solution for submodular potentials. When potentials are non-submodular, we show that important properties such as weak persistency hold for solution inferred by AC. AC is a polynomial time primal dual approximation algorithm for fixed clique size. We show experimentally that AC not only provides significantly better solutions in practice, it is an order of magnitude faster than message passing schemes like Dual Decomposition [19] and GTRWS [17] or Reduction based techniques like [10, 13, 14].
Enhancing Lifelogging Privacy by Detecting Screens

Low-cost, lightweight wearable cameras let us record (or 'lifelog') our lives from a 'first-person' perspective for purposes ranging from fun to therapy. But they also capture private information that people may not want to be recorded, especially if images are stored in the cloud or visible to other people. For example, recent studies suggest that computer screens may be lifeloggers' single greatest privacy concern, because many people spend a considerable amount of time in front of devices that display private information. In this paper, we investigate using computer vision to automatically detect computer screens in photo lifelogs. We evaluate our approach on an existing in-situ dataset of 36 people who wore cameras for a week, and show that our technique could help manage privacy in the upcoming era of wearable cameras.
Regulation of chemoresistance by the bcl-2 oncoprotein in non-Hodgkin's lymphoma and lymphocytic leukemia cell lines.

BACKGROUND The bcl-2 gene becomes activated by 14;18 chromosomal translocations in the majority of low-grade non-Hodgkin's lymphomas (NHLs) and is expressed at high levels in the absence of gene rearrangements in a high proportion of B-cell chronic lymphocytic leukemias (B-CLLs). The protein encoded by bcl-2 contributes to neoplastic cell expansion by prolonging cell survival through its ability to block programmed cell death (apoptosis). Because many chemotherapeutic drugs have been shown ultimately to kill tumor cells through mechanisms consistent with programmed cell death, we tested whether the relative levels of bcl-2 oncoprotein influence the sensitivity of lymphoma and leukemia cell lines to killing by conventional cytotoxic drugs commonly used in the treatment of cancer. METHODS Leukemia cell lines with low levels of bcl-2 expression were stably infected with recombinant bcl-2 retroviruses to achieve elevations in bcl-2 protein levels. Lymphoma cell lines with high levels of bcl-2 expression as the result of 14;18 translocations were either stably transfected with inducible bcl-2 antisense expression plasmids or treated with bcl-2 antisense oligonucleotides to achieve reductions in bcl-2 protein levels. The sensitivity of these genetically modified cells to killing by various antineoplastic drugs was then determined. RESULTS Gene transfer-mediated elevations in bcl-2 protein levels in lymphocytic leukemia cell lines was correlated with markedly elevated resistance to killing by all cytotoxic drugs tested. Conversely, antisense-mediated reductions in bcl-2 protein levels in t(14;18)-containing NHL cell lines resulted in enhanced sensitivity to all anticancer drugs. CONCLUSIONS The relative levels of bcl-2 oncoprotein represent one of the key determinants of the sensitivity of lymphocytic cells to killing by essentially all drugs currently available for the treatment of cancer.
The influences of distance on health facility delivery in rural Zambia

Skilled attendance at delivery is crucial for decreasing maternal and neonatal mortality. My literature review showed that epidemiological research on factors influencing whether women receive skilled attendance has so far been hampered by a lack of data on health service availability, and is often restricted to investigating household and individual factors. Distance to health services, however, is likely to play an important role. The availability of geographic coordinates in both national household survey, population census and health facility census in Zambia provides the opportunity to combine user and provider information on a large scale. These datasets were linked to investigate the influence that distance has on place of delivery, while adjusting for other influential factors such as education, wealth and autonomy in a multilevel model. Classifying Zambian health facilities according to their level of delivery care showed that 88% of facilities are not staffed or equipped to provide even Basic Emergency Obstetric Care (EmOC) and therefore cannot save a mother's life in case of complications. Around half of the Zambian population lives further than 15km from a Basic EmOC facility; less than 10% in urban areas and over 70% in rural areas. Using data from over 3000 rural births, I demonstrate that the odds of delivering in a facility are 4 times higher within 1km of a facility as compared to 20km, and additionally 2.5 times higher if that facility offers Comprehensive EmOC rather than substandard care. If all mothers lived within 5km of Basic EmOC, 16% of home deliveries could be avoided, a population attributable fraction of similar magnitude as for education or wealth. Lack of geographical access to EmOC is a key factor explaining why most rural deliveries in Zambia still occur at home without skilled care; this needs to be addressed to lower maternal and neonatal mortality.
A new feature and associated optimal spatial filter for EEG signal classification: Waveform Length

In this paper, we introduce Waveform Length (WL), a new feature for ElectroEncephaloGraphy (EEG) signal classification which measures the signal complexity. We also propose the Waveformlength Optimal Spatial Filter (WOSF), an optimal spatial filter to classify EEG signals based on WL features. Evaluations on 15 subjects suggested that WOSF with WL features provide performances that are competitive with that of Common Spatial Patterns (CSP) with Band Power (BP) features, CSP being the optimal spatial filter for BP features. More interestingly, our results suggested that combining WOSF with CSP features leads to classification performances that are significantly better than that of CSP alone (80% versus 77% average accuracy respectively).
Towards Automotive Software Health Management

Integrated Vehicle Health Management (IVHM) covers frameworks for detecting, diagnosing, and mitigating faults in hardware and structures in aerospace systems. Software Health Management (SHM) applies the goals of IVHM to software-intensive systems to detect software faults in real-time and to mitigate them. In this position paper, we describe the needs and challenges of SHM in automotive systems.
Heat conduction through a trapped solid: the effect of structural changes on the thermal conductance

We study the conduction of heat across a narrow solid strip trapped by an external potential and in contact with its own liquid. Structural changes, consisting of addition and deletion of crystal layers in the trapped solid, are produced by altering the depth of the confining potential. Nonequilibrium molecular dynamics simulations and, wherever possible, simple analytical calculations are used to obtain the thermal resistance in the liquid, solid and interfacial regions (Kapitza or contact resistance). We show that these layering transitions are accompanied by sharp jumps in the contact thermal resistance. Dislocations, if present, are shown to increase the thermal resistance of the strip drastically.