Miracle-dz/UniFAR-FTUs huggingface dataset:
Deletions in guaBA and htrA but not clpX or rfaL constitute a live-attenuated vaccine strain of Salmonella Newport to protect against serogroup C2-C3 Salmonella in mice

ABSTRACT Non-typhoidal Salmonella (NTS) are a leading cause of foodborne infections worldwide, and serogroups B, C1, C2-C3 and D are the most common serogroups associated with human disease. While live vaccine candidates that protect against S. Typhimurium (serogroup B) and S. Enteritidis (serogroup D) have been described by us and others, far less effort has been directed towards vaccines that target either serogroup C1 or C2-C3 Salmonella. Here we describe a Salmonella Newport-based live-attenuated vaccine (serogroup C2-C3). Deletion of the genes clpX or rfaL, previously used in live vaccines to attenuate S. Typhimurium and/or S. Enteritidis, failed to attenuate S. Newport. However, we found that deletion of either guaBA or htrA raised the 50% lethal dose of S. Newport in an intraperitoneal infection model in BALB/c mice. Our live-attenuated vaccine candidate CVD 1966 (S. Newport ΔguaBA ΔhtrA) elicited strong antibody responses against COPS, flagellin and outer membrane proteins when administered intraperitoneally or orally. Following lethal challenge with the parental virulent strain of S. Newport, we observed vaccine efficacies of 53% for immunization via the intraperitoneal route and 47% for immunization via the oral route. Following intraperiteonal immunization, the vaccine also significantly reduced the bacterial burden of challenge organisms in the liver and spleen. Interestingly, reducing the LPS chain length by deleting rfaL did not induce a stronger immune response towards surface antigens, and failed to elicit any protection against lethal homologous challenge. In conclusion, we have developed a live-attenuated Salmonella serogroup C2-C3 vaccine that we are further evaluating.
Effect of chronic heat stress on some physiological and immunological parameters in different breed of broilers

ABSTRACT The differences in physiological and immunological parameters and pathological damage to organ tissues exposed to chronic heat stress provide the basis for evaluating heat resistance of different chicken breeds (white recessive rock [WRR] and The Lingshan [LS]). Ninety broilers of each breed were divided equally into a chronic heat stress group and a no heat stress group. The effects of chronic heat stress on the physiological and immunological parameters of broilers were analyzed using flow cytometry, ELISA, RT-qPCR, etc. Under heat stress conditions: (1) H and H/L values were significantly increased (P < 0.01) in the 2 breeds, and were higher in the WRR broilers than in the LS broilers at a late stage (P < 0.05). Although the corticosterone levels were also significantly increased (P < 0.01) in both breeds, they were lower in the 49 d WRR broilers than in the LS broilers (P < 0.01). The number of leukocytes were significantly increased in the 49 d WRR broilers (P < 0.01), whereas the number of CD3+, CD8+ cells, and erythrocytes were significantly reduced (P < 0.05). A significantly (P < 0.01) lower number of CD3+, CD4+ T-lymphocytes, and CD4+/CD8+ were present in WRR compared to that in the LS broilers. (2) The HSP70 transcript was significantly increased in the WRR broilers (P < 0.01), and was higher than the level in the LS broilers. The expression level of HSP70 protein was significantly (P < 0.05) increased in WRR broilers. (3) The WRR broilers developed cardiac and leg muscle inflammatory cellular hyperplasia and local inflammatory lesions, as well as cerebral meningitis and inflammatory hyperplasia of the brain tissue. The LS broilers developed mild cerebral inflammatory hyperplasia and mild inflammatory cellular proliferation in the leg muscle. In conclusion, under heat stress conditions, the relative physiological and immunological parameters were worse in the WRR broilers than in the LS broilers. The WRR broilers showed poor heat tolerance as evidenced from the expression of HSP70 and the extent of histopathological damages.
Analysis of cluster heads positions in stable election protocol for Wireless Sensor Network

In Wireless Sensor Network (WSN) the energy consumed by each sensor is an important parameter, which affects the lifetime of the network. Therefore, different routing protocols have been developed to extend the lifetime of WSN by efficient use of energy of the sensors, what can also limit the energy used by the whole Internet of Thing (IoT) network. Nowadays, SEP (Stable Election Protocol) and LEACH (Low-energy adaptive clustering hierarchy) are the best known hierarchical routing protocols for maintaining power consumption in WSN. In SEP and also in LEACH, some nodes work as Cluster Heads (CH), which combine the records of their cluster members and transmit it to the sink. In this paper, we propose a modified Stable Election Protocol with a new algorithm for choosing cluster heads from normal nodes and advanced nodes. In each cluster, the node which is in the center of the cluster area is chosen as a cluster head. In our previous work [5] this algorithm was implemented for LEACH protocol. Finally, the results obtained for modified SEP and modified LEACH protocols have been compared.
Anti-fraud system on the basis of data mining technologies

The article is devoted to the issues of increasing the efficiency of transaction monitoring systems (TMS). The main types of TMS with their advantages and disadvantages are considered, and various algorithms of data mining used in this field were also considered. On the basis of the analysis of systems and algorithms, three classifiers were chosen: a multilayer perceptron (MLP), a classifier based on a random forest and a method of support vectors. The selected classifiers were tested on full-scale data. The best indicators were noted for the classifier on the basis of a random forest. The structure of the system for collecting and analyzing information about the user environment (UE) has been developed, which makes it possible to accumulate data about the UE, to mark use cases in manual and automatic modes and to build a database of images for training neural network classifiers. An algorithm for analyzing the information collected about the UE based on cluster analysis is developed.
Integrating Predictions from Neural-Network Relation Classifiers into Coreference and Bridging Resolution

Cases of coreference and bridging resolution often require knowledge about semantic relations between anaphors and antecedents. We suggest state-of-the-art neural-network classifiers trained on relation benchmarks to predict and integrate likelihoods for relations. Two experiments with representations differing in noise and complexity improve our bridging but not our coreference resolver.
Design of a multi-sided platform supporting CPS deployment in the automation market

CPS technologies are already mature at European level, but adoption in small & middle enterprises is constrained by a still emerging value chain and by the challenging transformation of manufacturing processes that their deployment in a manufacturing system requires. As a matter of fact, the CPS growing market potential is scarcely supported by tools able to sustain the solid ecosystem required for a relevant market uptake. This issue becomes even more constraining the moment the concept of CPS is extended and aggregated to propose cyber-physical machines and manufacturing systems, where the complexity of the controlling intelligence and of the digital counterpart explodes. This paper aims at describing how the design and implementation of a multi-sided platform (MSP) for CPS deployment within the automation sector can provide the technological background to incentivize their adoption. In fact, the market needs an economic support to accelerate the transition towards new paradigms for the development of the software components of a mechatronic system. Developing an infrastructure on the top of which the CPS value chain can be instantiated and orchestrated, we provide the technical means to incentivize the creation of such an ecosystem able to support SMEs in their transition towards Industry 4.0.
Religiosity: Protective or Risk Factor for Posttraumatic Distress Among Adolescents Who Were Exposed to Different Types of Acts of Political Violence

This study examined the potential moderating effects of religiosity on the associations between exposure to acts of political violence and posttraumatic stress symptoms (PTS) among Jewish adolescents in Israel. In addition, it examined whether self-reported physical and interpersonal exposure to acts of political violence predicts PTS symptoms beyond the objective exposure effects (i.e., the proximity of participants’ place of residence to high-, moderate-, or low-intensity political violence). A representative sample of 2,992 Jewish high school students (Grades 10 and 11) was taken. We used self-reporting to measure the level of religiosity and the Impact of Events Scale–Revised (IES-R) to measure PTS symptoms. Results show that self-reported exposure to acts of political violence adds a significant additional amount of variance to the prediction of PTS symptoms after objective exposure is already included in the regression equation. Religiosity was found as a risk factor for PTS symptoms such that the greater the religiosity of the adolescents, the higher their PTS symptoms. Therefore, prevention interventions should target the vulnerable group of religious Jewish adolescents.
Functional Partitioning of Genomic Variance and Genome-Wide Association Study for Carcass Traits in Korean Hanwoo Cattle Using Imputed Sequence Level SNP Data

Quantitative traits are usually controlled by numerous genomic variants with small individual effects, and variances associated with those traits are explained in a continuous manner. However, the relative contributions of genomic regions to observed genetic variations have not been well explored using sequence level single nucleotide polymorphism (SNP) information. Here, imputed sequence level SNP data (11,278,153 SNPs) of 2109 Hanwoo steers (Korean native cattle) were partitioned according to functional annotation, chromosome, and minor allele frequency (MAF). Genomic relationship matrices (GRMs) were constructed for each classified region and fitted in the model both separately and together for carcass weight (CWT), eye muscle area (EMA), backfat thickness (BFT), and marbling score (MS) traits. A genome-wide association study (GWAS) was performed to identify significantly associated variants in genic and exon regions using a linear mixed model, and the genetic contribution of each exonic SNP was determined using a Bayesian mixture model. Considering all SNPs together, the heritability estimates for CWT, EMA, BFT, and MS were 0.57 ± 0.05, 0.46 ± 0.05, 0.45 ± 0.05, and 0.49 ± 0.05, respectively, which reflected substantial genomic contributions. Joint analysis revealed that the variance explained by each chromosome was proportional to its physical length with weak linear relationships for all traits. Moreover, genomic variances explained by functional category and MAF class differed greatly among the traits studied in joint analysis. For example, exon regions had larger contributions for BFT (0.13 ± 0.08) and MS (0.22 ± 0.08), whereas intron and intergenic regions explained most of the total genomic variances for CWT and EMA (0.22 ± 0.09–0.32 ± 0.11). Considering different functional classes of exon regions and the per SNP contribution revealed the largest proportion of genetic variance was attributable to synonymous variants. GWAS detected 206 and 27 SNPs in genic and exon regions, respectively, on BTA4, BTA6, and BTA14 that were significantly associated with CWT and EMA. These SNPs were harbored by 31 candidate genes, among which TOX, FAM184B, PPARGC1A, PRKDC, LCORL, and COL1A2 were noteworthy. BayesR analysis found that most SNPs (>93%) had very small effects and the 4.02–6.92% that had larger effects (10-4 × σA2, 10-3 × σA2, and 10-2 × σA2) explained most of the total genetic variance, confirming polygenic components of the traits studied.
The research of excitation source in FDTD method for waveguide

Excitation source is an important part in finite difference time domain (FDTD) simulations. There are several kinds of excitation source, such as the hard field source, the transparent current source, the total field/scattered field (TF/SF) source, the transparent field source and so on. When simulating the waveguide, we need a transparent source to keep the exciting field at the source grids as desired in some cases, for example simulating the waveguide's discontinuities. In this paper, we proposed a new transparent field source without the auxiliary FDTD simulation, which can be more timesaving.
CAVITY SOLITONS: DISSIPATIVE STRUCTURES IN NONLINEAR PHOTONICS

In the first part of this article, we briefly overview the formation of dissipative structures in various out of equilibrium systems. In the second part, we address the formation of localized structures often called cavity solitons in nonlinear optics. We will focus on the interaction between cavity solitons, the polarization properties, and the effect of delay feedback control. The following systems will be discussed: passive resonators such as optical fibers, whispering gallery mode cavities, integrated ring resonators, left-handed materials, and vertical cavity surface emitting lasers with or without saturable absorption. The year 2017 marks the 50th anniversary of the scientific concept named dissipative structures that was put forward by Ilya Prigogine. This paper is dedicated to honor the memory of Ilya Prigogine on the occasion of the anniversary in 2017 of 100 years from his birthday. The aim of this article is to provide a list of selected subjects on some important properties of cavity solitons as generic examples of dissipative structures and their applicability in diverse fields of photonics and nonlinear sciences. Therefore, this paper is meant for active research physicists and engineers working in nonlinear optics and photonics and wishing to have a quick overview of recent developments in terms of the applicability of cavity solitons.
Distributed control architecture for dynamic reconfiguration: Flexible assembly line case study

This article presents the development of a distributed manufacturing case study enhanced with features that enable flexibility during the production process and the capability to continue the production process in case of fault scenarios. The approach described in this paper presents solutions to achieve the production of customized products, handle changes in product order, and minimize downtime and avoid total shutdown of the manufacturing system due to the occurrence of failures during the production process.
Electrical distribution network's failure analysis based on weather conditions

The failure detection and response time for failures in electrical distribution networks are key elements for proper power management in distribution companies. The reliability of electrical distribution is strictly related with weather conditions especially in overhead lines. Severe weather conditions can rapidly increase failure rates in distribution networks where company responses for failures may delayed consequently. In this study, electrical distribution network statistics of Beda; Company for Gaziosmanpasa district which contains highest overhead line population in Istanbul are investigated. These statistics are collected from failure management system in Bedas Distribution Company between 2014 and 2016. Especially electrical connector and oxidation failure rates are analyzed for different weather conditions. These statistics are compared with first four months of year 2017 which exhibit severe weather conditions and heavy falls. This study reveals the relationship between different weather conditions and failures in electrical distribution network which can be utilized for predictive management for distribution companies in terms of failure elimination and quick failure response.
The intra-neuroendoscopic technique: a new method for rapid removal of acute severe intraventricular hematoma

The mortality rate of acute severe intraventricular hematoma is extremely high, and the rate of disability in survivors is high. Intraventricular hematoma has always been a difficult problem for clinical treatment. Although minimally invasive endoscopic hematoma evacuation is widely used to treat this disease, the technique still has room for improvement. Equipment for the intra-neuroendoscopic technique (INET) consists of two of our patented inventions: a transparent sheath (Patent No. ZL 200820046232.0) and a hematoma aspirator (Patent No. ZL 201520248717.8). This study explored the safety and efficacy of INET by comparing it with extraventricular drainage in combination with urokinase thrombolytic therapy. This trial recruited 65 patients with severe intraventricular hemorrhage, including 35 (19 men and 16 women, aged 53.2 ± 8.7 years) in the INET group and 30 (17 men and 13 women, aged 51.5 ± 7.9 years) in the control group (extraventricular drainage plus urokinase thrombolytic therapy). Our results showed that compared with the control group, the INET group exhibited lower intraventricular hemorrhage volumes, shorter intensive care-unit monitoring and ventricular drainage-tube placement times, and fewer incidences of intracranial infection, secondary bleeding, and mortality. Thus, the prognosis of survivors had improved remarkably. These findings indicate that INET is a safe and efficient new method for treating severe intraventricular hematoma. This trial was registered with ClinicalTrials.gov (NCT02515903).
Spectrum Efficient Resource Management for Multi-Carrier-Based NOMA Networks: A Graph-Based Method

This letter investigates the spectrum efficient resource management problem (SERMP) for non-orthogonal multiple access-based uplink networks. Specifically, we take the decoding threshold of successive interference cancellation into account and formulate the SERMP as a sum-rate maximization problem by jointly considering the user pairing, channel assignment, and power control. For tackling this hard problem, we first analytically get the optimal transmit power for each user pair with given channel assignments. Afterward, we tactfully transform the primal problem into a maximum weighted independent set issue in graph theory, based on which we devise a low-complexity resource allocation algorithm. Finally, simulation results exhibit the performance improvement of our algorithm against other schemes in terms of data rate and number of supported users.
The Vertical-Cavity Surface-Emitting Laser as a Sensing Device

We show that a change to the quality (Q) factor of a laser diode cavity affects the electrical properties of the device. The mechanism is demonstrated experimentally and numerically via a 980-nm InGaAs/GaAs oxide-aperture vertical-cavity surface-emitting laser (VCSEL) wherewith thin, sub-half-lambda-thick Six Ny layers are deposited on top of the VCSEL's top-coupling distributed Bragg reflector (DBR) mirror to modify the DBR's power reflectance. The presence of such a mechanism enables the detection of a substance that rests on or is in close proximity to the exposed DBR when the substance modifies the Q factor of the laser diode. As an example, we numerically analyze the influence of the change of the refractive index and absorption of a substance in the proximity of a 1651-nm AlInGaAs/InP VCSEL with a top mirror in the form of a monolithic subwavelength high-index contrast grating (MHCG). Such a design enables the detection of methane near the MHCG by changing the properties of the resonating light in the proximity of the grating. We show that this sensing mechanism enables the construction of a new compact optical sensing system without the need for a photodetector.
An Educational Intervention to Improve Inpatient Documentation of High-risk Diagnoses by Pediatric Residents.

OBJECTIVES Diagnoses extracted from physician notes are used to calculate hospital quality metrics; failure to document high-risk diagnoses may lead to the appearance of worse-than-expected outcomes for complex patients. Academic hospitals often rely on documentation authored by trainees, yet residents receive little training in this regard. In this study, we evaluate inpatient pediatric resident notes to determine which high-risk diagnoses are commonly missed and assess the efficacy of a multitiered intervention to improve the documentation of these diagnoses. METHODS In a baseline review of 220 charts, 13 frequently missed high-risk diagnoses were identified in 2013. Interventions began in 2014, including physician education and reference cards. The intervention also included note template prompts for 4 of the diagnoses. Using a standardized rubric, we reviewed charts for 3 years (2013, 2014, and 2015). The average within-disease probability of missed high-risk diagnoses was compared across time. RESULTS There was a decrease in the probability of undocumented target high-risk diagnoses after the intervention (52% vs 36% in 2014 [odds ratio = 0.51; P < .001] and 37% in 2015 [odds ratio = 0.50; P < .001]). Documentation of diagnoses prompted by the note template was not significantly better than those targeted by the other interventions alone (P = .55). CONCLUSIONS Pediatric residents were significantly less likely to omit a high-risk diagnosis in their notes after implementation of our documentation improvement program, suggesting that curriculum development is an effective method of improving documentation, with the goal of improving the accuracy of health systems performance indices.
Encrypted data ordering with functional encryption

For security and privacy, often the user's data are stored on a cloud storage server in an encrypted form. Such data however, are required to be processed in terms of search queries, aggregation, clustering or classification. For better data analysis, the stored data on the server and a result of the processed data should be in lexicographic order. The conventional recourse such as offloading-decryption-ordering, may not be an efficient mechanism for huge data collection since it involves large communication overhead and breach of data privacy. Functional Encryption (FE) provides a viable solution as it offers encrypted data processing at the remote server site while preserving the privacy of the processed data. In this paper, we propose an improvised functional encryption for encrypted data ordering that takes as input multiple ciphertexts and orders them at the server site, without compromising data privacy. As ordering involves at least two data, we formalize an order function using multi-input functional encryption with obfuscation. The proposed approach, Multi-Input Functional Encryption for Ordering (MIFEO) runs an order function on multiple ciphertexts at the server site, arranges them in order and generates an ordered set of ciphertexts. Using online E-health system as a case study, we demonstrate the applicability of the proposed MIFEO scheme in a practical scenario.
Risk sensitive estimation using cubature quadrature points for system with unmodeled bias

In this paper risk sensitive estimation based upon cubature quadrature rule for system with model uncertainty due to unmodeled bias is discussed. The system used here is three dimensional discrete time Lorenz attractor, one of the classic icons in non-linear dynamics. A brief discussion over risk sensitive estimation has been given. Risk sensitive estimation using cubature quadrature rule has been discussed. The improvement in performance of this risk sensitive estimator in comparison to its risk neutral counterpart has been shown for system with unmodeled bias.