Miracle-dz/UniFAR-FTUs huggingface dataset:
Phage Types and Genotypes of Shiga Toxin-Producing Escherichia coli O157:H7 Isolates from Humans and Animals in Spain: Identification and Characterization of Two Predominating Phage Types (PT2 and PT8)

ABSTRACT Phage typing and DNA macrorestriction fragment analysis by pulsed-field electrophoresis (PFGE) were used for the epidemiological subtyping of a collection of Shiga toxin-producing Escherichia coli (STEC) O157:H7 strains isolated in Spain between 1980 and 1999. Phage typing distinguished a total of 18 phage types among 171 strains isolated from different sources (67 humans, 82 bovines, 12 ovines, and 10 beef products). However, five phage types, phage type 2 (PT2; 42 strains), PT8 (33 strains), PT14 (14 strains), PT21/28 (11 strains), and PT54 (16 strains), accounted for 68% of the study isolates. PT2 and PT8 were the most frequently found among strains from both humans (51%) and bovines (46%). Interestingly, we detected a significant association between PT2 and PT14 and the presence of acute pathologies. A group of 108 of the 171 strains were analyzed by PFGE, and 53 distinct XbaI macrorestriction patterns were identified, with 38 strains exhibiting unique PFGE patterns. In contrast, phage typing identified 15 different phage types. A total of 66 phage type-PFGE subtype combinations were identified among the 108 strains. PFGE subtyping differentiated between unrelated strains that exhibited the same phage type. The most common phage type-PFGE pattern combinations were PT2-PFGE type 1 (1 human and 11 bovine strains), PT8-PFGE type 8 (2 human, 6 bovine, and 1 beef product strains), PT2-PFGE subtype 4A (1 human, 3 bovine, and 1 beef product strains). Nine (29%) of 31 human strains showed phage type-PFGE pattern combinations that were detected among the bovine strains included in this study, and 26 (38%) of 68 bovine strains produced phage type-PFGE pattern combinations observed among human strains included in this study, confirming that cattle are a major reservoir of strains pathogenic for humans. PT2 and PT8 strains formed two groups which differed from each other in their motilities, stx genotypes, PFGE patterns, and the severity of the illnesses that they caused.
pproximate Re A Personal

In this presentation we provide a personal perspective of the progress made in the field of approximate reasoning systems. Because of time and space limitations, we will limit the scope of our discussion to cover the most notable trends and efforts in reasoning with uncertainty and vagueness. The existing approaches to representing this type of information can be subdivided in two basic categories according to their qualitative or quantitative characterizations of uncertainty. Models based on qualitative approaches are usually designed to handle the aspect of uncertainty derived from the incompleteness of the information, such as Reasoned Assumptions (Doyle, 1983), and Default Reasoning (Reiter, 1980). With a few exceptions, they are generally inadequate to handle the case of imprecise information, as they lack any measure to quantify confidence levels (Doyle, 1983). A few approaches in this group have addressed the representation of uncertainty, using either a formal representation, such as Knowledge and Belief (Halpern and Moses, 1986), or a heuristic representation, such as the Theory of Endorsements (Cohen, 1985). We will further limit our presentation by focusing on the development the quantitative approaches. Over the past few years, quantitative uncertainty management has received a vast amount of attention from the researchers in the field, (Shachter et al., 1990, Henrion et al., 1990, Bonissone et al., 1991, D’Ambrosio et al., 1991), leading to the establishment of two well-defined approaches, that differ in the semantics of their numerical representation. One is the probabiZ&ic reasoning approach, based on probability theory. The other one is the possibilistic reasoning approach, based on the semantics of fuzzy sets and many-valued logics. In this paper we will illustrate and compare these approaches and we will conclude with a review of efforts aimed at improving their real-time performance.
Nanomodification of mineral trioxide aggregate for enhanced physiochemical properties.

AIM To analyse the physicochemical properties of a Nano white mineral trioxide aggregate (NWMTA) and compare it with white mineral trioxide aggregate (WMTA). METHODOLOGY White mineral trioxide aggregate and NWMTA were prepared and mixed according to the manufacturer's instructions. Surface area of powder before hydration, setting time, X-ray diffraction and microhardness at pH values of 4.4 and 7.4 were evaluated by Brunauer-Emmett-Teller, ISO Specification no.6876, Vickers microhardness, and energy-dispersive X-ray spectroscopy equipped with X-ray colour (dot) map for both cements. anova and Mann-Whitney were used for statistical analysis at a significance level of 0.5. RESULTS The mean ± SD of surface area and setting time were 1.8 ± 0.2 m(2) g(-1) and 43 ± 2 min for WMTA and 7.8 ± 1.2 m(2) g(-1) and 6 ± 1 min for NWMTA, respectively. Mean ± SD of Microhardness were 16 ± 2, 51 ± 1, 69 ± 1 and 81 ± 2 for WMTA at pH values of 4.4 and 7.4 and for NWMTA correspondingly. Numbers of open porosity over the surface were 88 ± 24 and 44 ± 13 for WMTA and NWMTA, respectively. Statistical tests revealed significant differences between the groups (P < 0.001) in surface area, setting time and surface hardness for both cements. Uniform distribution of strontium was only observed in NWMTA. However, other compounds were not significantly different. CONCLUSION Increasing surface area of powder can reduce setting time and increase microhardness even at lower pH values after hydration.
Simultaneous Maxillary and Mandibular Brown Tumors as the First Presentation of Secondary Hyperparathyroidism

Brown tumor represents a serious and late bony complications of advanced hyperparathyroidism with a frequency of 1.5–1.75 percent in secondary hyperparathyroidism and 3–4 percent in primary hyperparathyroidism. Here we describe an extremely rare case of a 19-year-old male patient with a brown tumor localised in the maxilla and mandibular due to secondary hyperparathyroidism compromising mastication, phonation and social ease of the patient. An early diagnosis and a timely parathyroidectomy in a medically resistant hyperparathyroidism are an optimal option to control the growth of the bony lesion
Two separate motifs cooperate to target stathmin-related proteins to the Golgi complex

The appropriate targeting of membrane-associated proteins involves a diversity of motifs including post-translational modifications and specific protein sequences. Phosphoproteins of the stathmin family are important regulators of microtubule dynamics, in particular in the developing and mature nervous system. Whereas stathmin is cytosolic, SCG10, SCLIP and the splice variants RB3/RB3′/RB3″ are associated with Golgi and vesicular membranes, through their palmitoylated N-terminal A domains. In order to identify essential motifs involved in this specific targeting, we examined the subcellular distribution of various subdomains derived from domain A of SCG10 fused with GFP. We show that the Golgi localization of SCG10 results from the cooperation of two motifs: a membrane-anchoring palmitoylation motif and a newly identified Golgi-specifying sequence. The latter displayed no targeting activity by itself, but retained a Golgi-specifying activity when associated with another membrane-anchoring palmitoylation motif derived from the protein GAP-43. We further identified critical residues for the specific Golgi targeting of domain A. Altogether, our results give new insight into the regulation of the subcellular localization of stathmin family proteins, an important feature of their physiological functions in differentiating and mature neural cells. More generally we provide new information on essential mechanisms of functional protein subcellular targeting.
E-CARP: An Energy Efficient Routing Protocol for UWSNs in the Internet of Underwater Things

With the advance of the Internet of Underwater Things, smart things are deployed under the water and form the underwater wireless sensor networks (UWSNs), to facilitate the discovery of vast unexplored ocean volume. A routing protocol, which is not expensive in packets forwarding and energy consumption, is fundamental for sensory data gathering and transmitting in UWSNs. To address this challenge, this paper proposes Enhanced CARP (E-CARP), which is an enhanced version of the channel-aware routing protocol (CARP) developed by S. Basagni et al., to achieve the location-free and greedy hop-by-hop packet forwarding strategy. In general, CARP does not consider the reusability of previously collected sensory data to support certain domain applications afterward, which induces data packets forwarding which may not be beneficial to applications. Besides, the PING-PONG strategy in CARP can be simplified for selecting the most appropriate relay node at each time point, when the network topology is relatively steady. These two research problems have been addressed by our E-CARP. Simulation results validate that our technique can decrease the communication cost significantly and increase the network capability to a certain extent.
Trajectory tracking for rigid 3-pendulum with nonholonomic gears

In this paper a solution to the trajectory tracking problem for nonholonomic 3-pendulum has been presented. The proposed control algorithm takes into considerations the kinematics as well as the dynamics of the nonholonomic system. Kinematic controller is the Jiang & Nijmeijer controller for chained systems and dynamic controller is a version of the Oya et al. control algorithm. Theoretical considerations have been illustrated with simulations.
A novel training method based on variable structure systems theory for fuzzy neural networks

Uncertainty is an inevitable problem in real-time industrial control systems and, to handle this problem and the additional one of possible variations in the parameters of the system, the use of sliding mode control theory-based approaches is frequently suggested. In this paper, instead of using a conventional sliding mode controller, a sliding mode control theory-based learning algorithm is proposed to train the fuzzy neural networks in a feedback-error-learning structure. The parameters of the fuzzy neural network are tuned by the proposed algorithm not to minimize the error function but to ensure that the error satisfies a stable equation. The parameter update rules of the fuzzy neural network are derived, and the proof of the learning algorithm is verified by using the Lyapunov stability method. The proposed method is tested on a real-time servo system with time-varying and nonlinear load conditions.
Joshua 5.0: Sparser, Better, Faster, Server

We describe improvements made over the past year to Joshua, an open-source translation system for parsing-based machine translation. The main contributions this past year are signiﬁcant improvements in both speed and usability of the grammar extraction and decoding steps. We have also rewritten the decoder to use a sparse feature representation, enabling training of large numbers of features with discriminative training methods.
High-quality Protein Knowledge Resource: SWISS-PROT and TrEMBL

SWISS-PROT is a curated protein sequence database which strives to provide a high level of annotation (such as the description of the function of a protein, its domain structure, post-translational modifications, variants, etc.), a minimal level of redundancy and a high level of integration with other databases. Together with its automatically annotated supplement TrEMBL, it provides a comprehensive and high-quality view of the current state of knowledge about proteins. Ongoing developments include the further improvement of functional and automatic annotation in the databases including evidence attribution with particular emphasis on the human, archaeal and bacterial proteomes and the provision of additional resources such as the International Protein Index (IPI) and XML format of SWISS-PROT and TrEMBL to the user community.
Finite-element analysis of the stress distribution in a torsion test of full-size, structural lumber

Full-size structural lumber under torsion was analyzed using the finite-element method to determine stress distribution. A three-dimensional, homogeneous, orthotropic finite-element model was developed and analyzed using commercially available software, ANSYS®, to increase understanding of stress distribution and failure modes. Analyses revealed that uniform shear stress occurs within the shear span, which begins and ends at a distance of approximately two times the depth plus the grip distance away from each end of the specimen. In addition, finite-element analysis verified that the experimental shear-failure plane that occurs within the shear span is parallel to the grain. Shear slippage is also parallel to the grain, similar to the known shear-failure mode in specimens subjected to transverse loads. Based on results of this study, the torsion test is the best practical method to determine the pure shear strength of full-size, structural lumber.
Three-Class Mammogram Classification Based on Descriptive CNN Features

In this paper, a novel classification technique for large data set of mammograms using a deep learning method is proposed. The proposed model targets a three-class classification study (normal, malignant, and benign cases). In our model we have presented two methods, namely, convolutional neural network-discrete wavelet (CNN-DW) and convolutional neural network-curvelet transform (CNN-CT). An augmented data set is generated by using mammogram patches. To enhance the contrast of mammogram images, the data set is filtered by contrast limited adaptive histogram equalization (CLAHE). In the CNN-DW method, enhanced mammogram images are decomposed as its four subbands by means of two-dimensional discrete wavelet transform (2D-DWT), while in the second method discrete curvelet transform (DCT) is used. In both methods, dense scale invariant feature (DSIFT) for all subbands is extracted. Input data matrix containing these subband features of all the mammogram patches is created that is processed as input to convolutional neural network (CNN). Softmax layer and support vector machine (SVM) layer are used to train CNN for classification. Proposed methods have been compared with existing methods in terms of accuracy rate, error rate, and various validation assessment measures. CNN-DW and CNN-CT have achieved accuracy rate of 81.83% and 83.74%, respectively. Simulation results clearly validate the significance and impact of our proposed model as compared to other well-known existing techniques.
New dielectric elastomers with improved properties for energy harvesting and actuation

New materials with large value for dielectric constant were obtained by using siloxane and chemically modified lignin. The modified lignin does not act as a stiffening filler material for the siloxane but acts as bulk filler, preserving the softness and low value of Young’s modulus specific for silicones. The measured values for dielectric constant compare positively with the ones for previously tested dielectric elastomers based on siloxane rubber or acrylic rubber loaded with ceramic nanoparticles. The new materials use the well-known silicone chemistry and lignin which is available worldwide in large amounts as a by-product of pulp and paper industry, making its manufacturing affordable. The prepared dielectric elastomers were tested for possible applications for wave, wind and kinetic body motion energy harvesting. Siloxane, lignin, dielectric
Robust stabilization of nonlinear uncertain plants with backlash or dead zone in the actuator

Actuator nonlinearities are often neglected in control system design, though they can remarkably affect systems performance. This paper presents sliding mode controllers able to robustly stabilize an intrinsically nonlinear uncertain plant, in the presence of dead zone or backlash in the actuator devices. These nonlinearities have been assumed uncertain, too, with known bounds on the parameters. In the case of backlash, two different approaches have been presented, obtained using a "quasistatic" and a "dynamic" description of the nonlinearity. Simulation results for a single input-single output (SISO) plant have been provided, addressing both the stabilization and the servo problem for a mechanical system representing a robot-like system with one link.
Robust speech endpoint detection based on MP3 file in various noisy environments

In audio retrieval, endpoint detection is a crucial step of front processing. This paper presents a MP3-based approach for robust endpoint detection under different types of noises. Firstly, the modified discrete cosine transform (MDCT) coefficients and scale factors (SCF) are extracted from MP3 file. Then, combined with the selection of SCF, a set of MDCT coefficients of white noise are used to enhance the speech signals. Finally, the spectral entropy-based method is applied to MDCT coefficients to gain the proposed parameter. Experimental results show that this algorithm has excellent performance in various adverse environments. Furthermore, for using the intermediate date of MP3 decoding, the proposed one has much less computational complexity.
Percutaneous transluminal angioplasty with or without stenting for femoropopliteal occlusions? A randomized controlled study.

BACKGROUND To investigate the-one year outcome of PTA and stenting and PTA alone for femoropopliteal occlusions. DESIGN Randomized prospective study METHODS 32 patients with femoropopliteal occlusions were randomized into two treatment groups: PTA and Strecker-stent (n=15) and PTA alone (n=17). The median age of the patients was 71 years. All patients had chronic limb ischaemia, 66% had tissue loss, 19% had rest pain and 15% had disabling claudication. The median ABPI was 0.45. The occlusion was confined to the superficial femoral artery in 30 cases and to the popliteal artery in 2 cases. The median length of the occlusions was 7.3 cm. Aspirin (ASA), 160 mg daily, was administrated postoperatively but no anticoagulation was used. The follow-up included: clinical examination, measurement of ABPI and control angiography at 12 months or earlier when necessary (20 patients). RESULTS There was no mortality or limb loss as a consequence of the treatment. There were six (16%) immediate major complications in five patients. In the PTA group, one patient had a myocardial infarction and three patients needed arteriography due to bleeding. In the stent group, one patient required arteriography and embolectomy. The one-year mortality was 6% and there were no amputations. Four patients (two in each group) were operated on with a femorodistal bypass. The rate of clinical improvement was 71% after PTA and stent and 60% after PTA alone (p=0.17). An increased ABPI (>0.10) was shown in 50% of the stent group and 61% in the PTA group (p=0.17). Angiographic re-occlusions were seen in 33% and 75% in the stent and PTA groups respectively (p=0.17), while the rate of restenosis was significantly higher in the stent group (50% vs 25%) (p=0.033). CONCLUSIONS Stenting following PTA for femoropopliteal occlusions does not significantly improve neither the clinical state nor the clinical/angiographic patency. The results do not justify any routine placement of stent following PTA in the successfully recanalized femoropopliteal arteries. The low rate of acceptance of a follow-up angiography indicates that this kind of study should preferably use duplex scanning instead of angiography for follow-up.
A Confidentiality-Preserving Search Technique for Encrypted Relational Cloud Databases

Database-as-a-Service is offered by many cloud service providers and could significantly reduce the IT infrastructure maintenance bills for enterprises. However, many hesitate migrating their data storage and processing to the cloud, and one of the reasons are data security issues. Encryption could provide sound security guarantees, but existing approaches often gravitate to one of the extremes: either high security and very limited functionality, or vice versa. This paper proposes a flexible database encryption scheme allowing multiple users to perform complex search-based queries, including cross-table joins, capable of utilizing database's indexing capabilities. Several proxy servers in between the user and the database server help to achieve this and make it all transparent for the user. The proposed solution demonstrates a practical performance level in most of our experiments.
Continuum Relaxation of Interacting Steps on Crystal Surfaces in 2+1 Dimensions

We study the relaxation of crystal surfaces in $2+1$ dimensions via the motion of interacting atomic steps. The goal is the rigorous derivation of the continuum limit. The starting point is a discrete scheme from the Burton, Cabrera, and Frank model, which accounts for diffusion of point defects (“adatoms”) on terraces and attachment‐detachment of atoms at step edges. It is shown that the macroscopic adatom current involves a tensor mobility, which describes different fluxes in directions parallel and transverse to step edges, although the physics of each terrace is assumed isotropic. When the steps are everywhere parallel (straight or circular) the tensor character of the mobility is unimportant; in the general $(2+1)$‐dimensional setting, however, it is crucial. Our methods consist of (i) the solution of the diffusion equation for adatoms via the separation of local space variables into “fast” and “slow,” and (ii) the treatment of the step chemical potential for a wide class of step energies and repulsi.
Volatiles from oral anaerobes confounding breath biomarker discovery

The levels of compounds in exhaled mouth air do not necessarily reflect levels in the systemic circulation as bacteria can bio-transform substrates to produce compounds within the mouth. This should be of concern to researchers measuring breath volatiles with the aim of diagnosing systemic or metabolic conditions as very little is known about the origin of many compounds detected on the breath. This pilot study investigated the production of volatile compounds by bacterial communities present within the mouth. Solid-phase micro-extraction was used to extract volatiles from the headspace gas of two Gram-positive and two Gram-negative bacterial cultures known to be present within the mouth and from tongue biofilm microflora. Analyses were undertaken using gas chromatography mass spectrometry. Between 64 and 82 volatile compounds were detected from sampling the headspace gas above each of the cultures. Gram-negative anaerobes were found to produce more volatile sulfur compounds (VSCs) and amines. Solobacterium moorei, a Gram-positive species was however found to produce higher levels of acids, hydrocarbons, alcohols and aldehydes than the other species studied. Tongue-scrape biofilm systems at lower pH gave more hydrocarbons, ketones and fatty acids whilst at higher pH more alcohols, aldehydes, VSCs and amines were detected in the headspace. The results show that a number of compounds detected in mouth breath are produced by anaerobic bacteria in tongue biofilms. Thus, the contribution of volatiles from oral anaerobes cannot be ignored and more research is required to identify the major source of breath compounds as this will help determine their clinical significance as indicators of systemic disease or metabolic disorders in the body.