Miracle-dz/UniFAR-FTUs huggingface dataset:
Microwave tomography: review of the progress towards clinical applications

Microwave tomography (MWT) is an emerging biomedical imaging modality with great potential for non-invasive assessment of functional and pathological conditions of soft tissues. This paper presents a review of research results obtained by the author and his colleagues and focuses on various potential clinical applications of MWT. Most clinical applications of MWT imaging have complicated, nonlinear, high dielectric contrast inverse problems of three-dimensional diffraction tomography. There is a very high dielectric contrast between bones and fatty areas compared with soft tissues. In most cases, the contrast between soft-tissue abnormalities (the target imaging areas) is less pronounced than between bone (fat) and soft tissue. This additionally complicates the imaging problem. In spite of the difficulties mentioned, it has been demonstrated that MWT is applicable for extremities imaging, breast cancer detection, diagnostics of lung cancer, brain imaging and cardiac imaging.
Information processing for learning systems: an action theoretical approach

For learning systems that interact with their environments, the more primitive concept of 'variety' will have to be used, instead of probability. Humans have a fundamental need for variety. This need for variety leads to a different interpretation of human behavior that is often classified as "errors". Variety is the basis to measure complexity of an activity. Complexity in the relationship between a learning system and human context can be expressed as incongruity. Incongruity is the difference between internal complexity of a learning system and the complexity of the context. Traditional concepts of information processing are models of homoeostasis on a basic level without learning. Activity and the irreversible learning process are driving forces that cause permanently in-homoeostasis in the relationship between a learning system and human context. A concept of information processing is presented that derives an inverted U-shaped function between incongruity and information. This concept leads to some design recommendations for man-machine systems.
Submodularity beyond submodular energies: Coupling edges in graph cuts

We propose a new family of non-submodular global energy functions that still use submodularity internally to couple edges in a graph cut. We show it is possible to develop an efficient approximation algorithm that, thanks to the internal submodularity, can use standard graph cuts as a subroutine. We demonstrate the advantages of edge coupling in a natural setting, namely image segmentation. In particular, for fine-structured objects and objects with shading variation, our structured edge coupling leads to significant improvements over standard approaches.
Analysis And Development Of Latent SemanticIndexing Techniques For Information Retrieval

The majority of information in a company is often useless or not equally interesting to everybody. The set of techniques called Analytical Business Intelligence provides a valid way to tackle the needs of information classification and of knowledge extraction that naturally arises inside a company. This paper proposes a suitable solution to make the digital resources useful, identifiable and accessible, through the creation of a Knowledge Base, i.e. a company-wide Intranet where techniques of Information Retrieval used by the Web are applied in order to reach a higher level of efficiency.
Candida albicans mannans mediate Streptococcus mutans exoenzyme GtfB binding to modulate cross-kingdom biofilm development in vivo

Candida albicans is frequently detected with heavy infection by Streptococcus mutans in plaque-biofilms from children with early-childhood caries (ECC). This cross-kingdom biofilm contains an extensive matrix of extracellular α-glucans that is produced by an exoenzyme (GtfB) secreted by S. mutans. Here, we report that mannans located on the outer surface of C. albicans cell-wall mediates GtfB binding, enhancing glucan-matrix production and modulating bacterial-fungal association within biofilms formed in vivo. Using single-molecule atomic force microscopy, we determined that GtfB binds with remarkable affinity to mannans and to the C. albicans surface, forming a highly stable and strong bond (1–2 nN). However, GtfB binding properties to C. albicans was compromised in strains defective in O-mannan (pmt4ΔΔ) or N-mannan outer chain (och1ΔΔ). In particular, the binding strength of GtfB on och1ΔΔ strain was severely disrupted (>3-fold reduction vs. parental strain). In turn, the GtfB amount on the fungal surface was significantly reduced, and the ability of C. albicans mutant strains to develop mixed-species biofilms with S. mutans was impaired. This phenotype was independent of hyphae or established fungal-biofilm regulators (EFG1, BCR1). Notably, the mechanical stability of the defective biofilms was weakened, resulting in near complete biomass removal by shear forces. In addition, these in vitro findings were confirmed in vivo using a rodent biofilm model. Specifically, we observed that C. albicans och1ΔΔ was unable to form cross-kingdom biofilms on the tooth surface of rats co-infected with S. mutans. Likewise, co-infection with S. mutans defective in GtfB was also incapable of forming mixed-species biofilms. Taken together, the data support a mechanism whereby S. mutans-secreted GtfB binds to the mannan layer of C. albicans to promote extracellular matrix formation and their co-existence within biofilms. Enhanced understanding of GtfB-Candida interactions may provide new perspectives for devising effective therapies to disrupt this cross-kingdom relationship associated with an important childhood oral disease.
Three algorithms for learning artificial neural network: A comparison for induction motor flux estimation

This paper presents a comparative study of three algorithms for learning artificial neural network. As neural estimator, back-propagation (BP) algorithm, uncorrelated real time recurrent learning (URTRL) algorithm and correlated real time recurrent learning (CRTRL) algorithm are used in the present work to learn the artificial neural network (ANN). The approach proposed here is based on the flux estimation of high performance induction motor drives. Simulation of the drive system was carried out to study the performance of the motor drive. It is observed that the proposed CRTRL algorithm based methodology provides better performance than the BP and URTRL algorithm based technique. The proposed method can be used for accurate measurement of the rotor flux.
Activation of the Antiviral Kinase PKR and Viral Countermeasures

The interferon-induced double-stranded (ds)RNA-dependent protein kinase (PKR) limits viral replication by an eIF2α-mediated block of translation. Although many negative-strand RNA viruses activate PKR, the responsible RNAs have long remained elusive, as dsRNA, the canonical activator of PKR, has not been detected in cells infected with such viruses. In this review we focus on the activating RNA molecules of different virus families, in particular the negative-strand RNA viruses. We discuss the recently identified non-canonical activators 5′-triphosphate RNA and the vRNP of influenza virus and give an update on strategies of selected RNA and DNA viruses to prevent activation of PKR.
Endoscopic Ultrasonography

Endoscopic ultrasonography (EUS) is nowadays a clinically relevant technology and its findings can have a major impact on patient management. This technique is currently indicated for staging digestive cancers, assessment of submucosal tumors, diagnosis of intestinal wall infiltrative diseases, common bile-duct stones and gut neuroendocrine tumors. As far as neoplasms are concerned, EUS appears to be a reliable and safe technique, thus making the physician able to plan either an aggressive surgical treatment, or a conservative palliative therapy. This is of the utmost importance in order to optimize medical-related costs, and to make the best therapeutic decision for each individual patient. EUS is also helpful in monitoring the course of a disease, as it is simple and virtually without complications. When EUS findings are not sufficient for a complete diagnosis, it is now possible to perform an EUS-guided fine-needle biopsy, which can allow a cytological diagnosis. Finally, some therapeutic endosonography-guided procedures are being increasingly adopted, such as cystoenterostomy, celiac plexus neurolysis, cholangio-pancreatography and selective injection of botulinum toxin in the muscle layer of the lower esophageal sphincter.
Nutrient enrichment, biodiversity loss, and consequent declines in ecosystem productivity

Anthropogenic drivers of environmental change often have multiple effects, including changes in biodiversity, species composition, and ecosystem functioning. It remains unknown whether such shifts in biodiversity and species composition may, themselves, be major contributors to the total, long-term impacts of anthropogenic drivers on ecosystem functioning. Moreover, although numerous experiments have shown that random losses of species impact the functioning of ecosystems, human-caused losses of biodiversity are rarely random. Here we use results from long-term grassland field experiments to test for direct effects of chronic nutrient enrichment on ecosystem productivity, and for indirect effects of enrichment on productivity mediated by resultant species losses. We found that ecosystem productivity decreased through time most in plots that lost the most species. Chronic nitrogen addition also led to the nonrandom loss of initially dominant native perennial C4 grasses. This loss of dominant plant species was associated with twice as great a loss of productivity per lost species than occurred with random species loss in a nearby biodiversity experiment. Thus, although chronic nitrogen enrichment initially increased productivity, it also led to loss of plant species, including initially dominant species, which then caused substantial diminishing returns from nitrogen fertilization. In contrast, elevated CO2 did not decrease grassland plant diversity, and it consistently promoted productivity over time. Our results support the hypothesis that the long-term impacts of anthropogenic drivers of environmental change on ecosystem functioning can strongly depend on how such drivers gradually decrease biodiversity and restructure communities.
Changing Business Dynamism and Productivity: Shocks vs. Responsiveness

The pace of job reallocation has declined in all U.S. sectors since 2000. In standard models, aggregate job reallocation depends on (a) the dispersion of idiosyncratic productivity shocks faced by businesses and (b) the marginal responsiveness of businesses to those shocks. Using several novel empirical facts from business microdata, we infer that the pervasive post-2000 decline in reallocation reflects weaker responsiveness in a manner consistent with rising adjustment frictions and not lower dispersion of shocks. The within-industry dispersion of TFP and output per worker has risen, while the marginal responsiveness of employment growth to business-level productivity has weakened. The responsiveness in the post-2000 period for young firms in the high-tech sector is only about half (in manufacturing) to two thirds (economy wide) of the peak in the 1990s. Counterfactuals show that weakening productivity responsiveness since 2000 accounts for a significant drag on a ggregate productivity.
Retrograde monosynaptic tracing reveals the temporal evolution of inputs onto new neurons in the adult dentate gyrus and olfactory bulb

Significance New neurons are constantly added to the hippocampus and the olfactory bulb. These neurons are believed to fulfill unique functions during their early life compared with mature neurons, which may depend on the way they are connected. Here we studied the stepwise integration of new neurons within these two brain areas using a rabies-virus–based synaptic tracing tool. Our study revealed that in both areas integration follows a similar logic, with adult-born neurons incorporating first into the local circuit before becoming innervated by long-range connections. This changing pattern of presynaptic connectivity likely contributes to adult-born neurons’ functions. Identifying the connectome of adult-generated neurons is essential for understanding how the preexisting circuitry is refined by neurogenesis. Changes in the pattern of connectivity are likely to control the differentiation process of newly generated neurons and exert an important influence on their unique capacity to contribute to information processing. Using a monosynaptic rabies virus-based tracing technique, we studied the evolving presynaptic connectivity of adult-generated neurons in the dentate gyrus (DG) of the hippocampus and olfactory bulb (OB) during the first weeks of their life. In both neurogenic zones, adult-generated neurons first receive local connections from multiple types of GABAergic interneurons before long-range projections become established, such as those originating from cortical areas. Interestingly, despite fundamental similarities in the overall pattern of evolution of presynaptic connectivity, there were notable differences with regard to the development of cortical projections: although DG granule neuron input originating from the entorhinal cortex could be traced starting only from 3 to 5 wk on, newly generated neurons in the OB received input from the anterior olfactory nucleus and piriform cortex already by the second week. This early glutamatergic input onto newly generated interneurons in the OB was matched in time by the equally early innervations of DG granule neurons by glutamatergic mossy cells. The development of connectivity revealed by our study may suggest common principles for incorporating newly generated neurons into a preexisting circuit.
Posttranscriptional changes of serum albumin: Clinical and prognostic significance in hospitalized patients with cirrhosis

Beside the regulation of fluid distribution, human serum albumin (HSA) carries other activities, such as binding, transport, and detoxification of many molecules. In patients with cirrhosis, HSA exhibits posttranscriptional alterations that likely affect its functions. This study aimed at identifying the structural HSA alterations occurring in cirrhosis and determining their relationship with specific clinical complications and patient survival. One hundred sixty‐eight patients with cirrhosis, 35 with stable conditions and 133 hospitalized for acute clinical complications, and 94 healthy controls were enrolled. Posttranscriptional HSA molecular changes were identified and quantified by using a high‐performance liquid chromatography/electrospray ionization mass spectrometry technique. Clinical and biochemical parameters were also recorded and hospitalized patients were followed for up to 1 year. Seven HSA isoforms carrying one or more posttranscriptional changes were identified. Altered HSA isoforms were significantly more represented in patients than in healthy controls. Conversely, the native, unchanged HSA isoform was significantly reduced in cirrhosis. Native HSA and most altered isoforms correlated with both Child‐Pugh and Model for End‐Stage Liver Disease scores. In hospitalized patients, oxidized and N‐terminal truncated isoforms were independently associated with ascites, renal impairment, and bacterial infection. Finally, the native HSA and cysteinylated/N‐terminal truncated isoforms were predictors of 1‐year survival, with greater prognostic accuracy than total serum albumin concentration. Conclusions: Extensive posttranscriptional changes of HSA, involving several molecular sites and increasing in parallel with disease severity, occur in patients with cirrhosis. Altered isoforms are independently associated with specific clinical complications, whereas the residual, native HSA isoform independently predicts patient survival. These findings support the concept of the “effective albumin concentration,” which implies that the global HSA function is related not only to its serum concentration, but also to the preservation of its structural integrity. (Hepatology 2014;60:1850–1859)
Predictive trend mining for social network analysis

This thesis describes research work within the theme of trend mining as applied to social network data. Trend mining is a type of temporal data mining that provides observation into how information changes over time. In the context of the work described in this thesis the focus is on how information contained in social networks changes with time. The work described proposes a number of data mining based techniques directed at mechanisms to not only detect change, but also support the analysis of change, with respect to social network data. To this end a trend mining framework is proposed to act as a vehicle for evaluating the ideas presented in this thesis. The framework is called the Predictive Trend Mining Framework (PTMF). It is designed to support "end-to-end" social network trend mining and analysis. The work described in this thesis is divided into two elements: Frequent Pattern Trend Analysis (FPTA) and Prediction Modeling (PM). For evaluation purposes three social network datasets have been considered: Great Britain Cattle Movement, Deeside Insurance and Malaysian Armed Forces Logistic Cargo. The evaluation indicates that a sound mechanism for identifying and analysing trends, and for using this trend knowledge for prediction purposes, has been established.
Autumn Migration of Myotis septentrionalis in Nebraska: Documentation of Fall Activity, Migratory Timing, and Distance Using Radio-telemetry

Few studies have investigated autumn migration of the northern long-eared myotis (Myotis septentrionalis). We conducted a two-year radio-tracking study of M. septentrionalis in southeastern Nebraska to document migration dates, activity in autumn, and movements to wintering sites. We observed that at least some M. septentrionalis migrate in late October and early November. Prior to migration, cold nights curtailed nighttime volant activity outside of roosts for M. septentrionalis. Two bats in this study did not emerge from their roost tree for seven consecutive nights during a period of colder weather. We monitored one bat leaving our research area on the night of 20 October 2015 and detected it 2.8 h later near a mine 41 km away. This observation likely represents a migratory movement, but more research is needed to have a better understanding of autumn migration in M. septentrionalis.
Functional Autonomy of Land and Sea Orientation Systems in Sea Turtle Hatchlings.

Sea turtle hatchlings emerge from underground nests on oceanic beaches and immediately confront two separate problems in orientation. First they must locate the ocean and crawl to it; then they must orient offshore while they swim out to sea in a migration lasting several days. Visual cues guide hatchlings from the nest to the sea (1, 2) but little is known about the cues used by turtles in the ocean. Nevertheless, the crawl across the beach has long been considered essential to swimming orientation because hatchlings released offshore without a crawl reportedly fail to orient seaward (3, 4). Here we report that hatchling leatherback (Dermochelys coriacea) and green (Chelonia mydas) sea turtles released offshore consistently swam toward approaching waves and oceanic swells. Wave tank experiments confirmed that swimming hatchlings oriented into waves. A crawl across the beach was not a prerequisite for wave orientation in either the field or lab, indicating that hatchling sea turtles possess two separate orientation systems, each based on different sensory cues and capable of functioning autonomously. The first guides hatchlings on land to the sea; the second, based on wave detection, functions during the ocean migration. In five field experiments with green turtles and five others with leatherbacks, we monitored the swimming orientation of hatchlings released at various distances offshore near Fort Pierce, Florida. A total of 45 green turtle and 48 leatherback hatchlings were tested. All experiments were conducted between July and September in 1988 and 1989. Hatchlings were obtained from nests deposited on beaches in the Fort Pierce area. Nests were checked daily
Bell Pepper Production in California

Author(s): Hartz, Tim; Cantwell, Marita; Lestrange, Michelle; Smith, Richard; Aguiar, José; Daugovish, Oleg | Abstract: Basic information for commercial bell pepper producers, including information on crop climatic requirements, varieties, planting, fertilization, harvest, and marketing channels.
The Johnson-Lindenstrauss Transform Itself Preserves Differential Privacy

This paper proves that an "old dog", namely - the classical Johnson-Lindenstrauss transform, "performs new tricks" - it gives a novel way of preserving differential privacy. We show that if we take two databases, D and D', such that (i) D'-D is a rank-1 matrix of bounded norm and (ii) all singular values of D and D' are sufficiently large, then multiplying either D or D' with a vector of iid normal Gaussians yields two statistically close distributions in the sense of differential privacy. Furthermore, a small, deterministic and public alteration of the input is enough to assert that all singular values of D are large. We apply the Johnson-Lindenstrauss transform to the task of approximating cut-queries: the number of edges crossing a (S, S)-cut in a graph. We show that the JL transform allows us to publish a sanitized graph that preserves edge differential privacy (where two graphs are neighbors if they differ on a single edge) while adding only O(|S|ϵ) random noise to any given query (w.h.p). Comparing the additive noise of our algorithm to existing algorithms for answering cut-queries in a differentially private manner, we outperform all others on small cuts (|S| = o(n)). We also apply our technique to the task of estimating the variance of a given matrix in any given direction. The JL transform allows us to publish a sanitized covariance matrix that preserves differential privacy w.r. t bounded changes (each row in the matrix can change by at most a norm-1 vector) while adding random noise of magnitude independent of the size of the matrix (w.h.p). In contrast, existing algorithms introduce an error which depends on the matrix dimensions.