Miracle-dz/UniFAR-FTUs huggingface dataset:
In Vitro Properties of BAL30072, a Novel Siderophore Sulfactam with Activity against Multiresistant Gram-Negative Bacilli

ABSTRACT BAL30072 is a new monocyclic β-lactam antibiotic belonging to the sulfactams. Its spectrum of activity against significant Gram-negative pathogens with β-lactam-resistant phenotypes was evaluated and was compared with the activities of reference drugs, including aztreonam, ceftazidime, cefepime, meropenem, imipenem, and piperacillin-tazobactam. BAL30072 showed potent activity against multidrug-resistant (MDR) Pseudomonas aeruginosa and Acinetobacter sp. isolates, including many carbapenem-resistant strains. The MIC90s were 4 μg/ml for MDR Acinetobacter spp. and 8 μg/ml for MDR P. aeruginosa, whereas the MIC90 of meropenem for the same sets of isolates was >32 μg/ml. BAL30072 was bactericidal against both Acinetobacter spp. and P. aeruginosa, even against strains that produced metallo-β-lactamases that conferred resistance to all other β-lactams tested, including aztreonam. It was also active against many species of MDR isolates of the Enterobacteriaceae family, including isolates that had a class A carbapenemase or a metallo-β-lactamase. Unlike other monocyclic β-lactams, BAL30072 was found to trigger the spheroplasting and lysis of Escherichiacoli rather than the formation of extensive filaments. The basis for this unusual property is its inhibition of the bifunctional penicillin-binding proteins PBP 1a and PBP 1b, in addition to its high affinity for PBP 3, which is the target of monobactams, such as aztreonam.
"ADICCIÓN" AL AZÚCAR: ¿MITO Ó REALIDAD? Revisión

A person with a “sweet tooth” has a weakness for sugar and is popularly considered addicted to sweets. However, so far there has been no systematic research on the existence of an “addiction” to a natural food. This concept of “addiction” to a food has gained great importance in developed countries where a fierce legal battle against the major fast food chains has started. It has been suggested that these companies use food strategies that promote an addictive behavior and could be responsible for one of the worst epidemics of our history, obesity. Experts in the field define drug addiction as a compulsive and uncontrollable use of a drug. They describe a series of stages in the acquisition and development of this disease. The first stage is bingeing and escalation of the drug use, followed by dependence, and a last stage determined by craving and relapse. In the present review, we will show a new animal model of sugar dependence with characteristics that mimic those of a drug of abuse. This research shows that foods, especially sugar, and drugs of addiction probably share the same neural systems.
Coordinated Decentralized Protocols for Failure Diagnosis of Discrete Event Systems

We address the problem of failure diagnosis in discrete event systems with decentralized information. We propose a coordinated decentralized architecture consisting of local sites communicating with a coordinator that is responsible for diagnosing the failures occurring in the system. We extend the notion of diagnosability, originally introduced in Sampath et al. (1995) for centralized systems, to the proposed coordinated decentralized architecture. We specify three protocols that realize the proposed architecture; each protocol is defined by the diagnostic information generated at the local sites, the communication rules used by the local sites, and the coordinator's decision rule. We analyze the diagnostic properties of each protocol. We also state and prove conditions for a language to be diagnosable under each protocol. These conditions are checkable off-line. The on-line diagnostic process is carried out using the diagnosers introduced in Sampath et al. (1995) or a slight variation of these diagnosers. The key features of the proposed protocols are: (i) they achieve, each under a set of assumptions, the same diagnostic performance as the centralized diagnoser; and (ii) they highlight the “performance vs. complexity” tradeoff that arises in coordinated decentralized architectures. The correctness of two of the protocols relies on some stringent global ordering assumptions on message reception at the coordinator's site, the relaxation of which is briefly discussed.
Improved color texture descriptors for remote sensing image retrieval

Abstract Texture features are widely used in image retrieval literature. However, conventional texture features are extracted from grayscale images without taking color information into consideration. We present two improved texture descriptors, named color Gabor wavelet texture (CGWT) and color Gabor opponent texture (CGOT), respectively, for the purpose of remote sensing image retrieval. The former consists of unichrome features computed from color channels independently and opponent features computed across different color channels at different scales, while the latter consists of Gabor texture features and opponent features mentioned above. The two representations incorporate discriminative information among color bands, thus describing well the remote sensing images that have multiple objects. Experimental results demonstrate that CGWT yields better performance compared to other state-of-the-art texture features, and CGOT not only improves the retrieval results of some image classes that have unsatisfactory performance using CGWT representation, but also increases the average precision of all queried images further. In addition, a similarity measure function for proposed representation CGOT has been defined to give a convincing evaluation.
Laser Acupuncture for Postoperative Pain Management in Cats

The aim of this study was to evaluate laser acupuncture as an adjuvant for postoperative pain management in cats. Twenty cats, undergoing ovariohysterectomy, were sedated with intramuscular (IM) ketamine (5 mg kg−1), midazolam (0.5 mg kg−1), and tramadol (2 mg kg−1). Prior to induction of anaesthesia, the subjects were randomly distributed into two groups of 10 cats: Laser: bilateral stomach 36 and spleen 6 acupoints were stimulated with infrared laser; Control: no acupuncture was applied. Anaesthesia was induced using intravenous propofol (4 mg kg−1) and maintained with isoflurane. Postoperative analgesia was evaluated by a blinded assessor for 24 h following extubation using the Dynamic Interactive Visual Analogue Scale and Multidimensional Composite Pain Scale. Rescue analgesia was provided with IM tramadol (2 mg kg−1), and the pain scores were reassessed 30 min after the rescue intervention. If the analgesia remained insufficient, meloxicam (0.2 mg kg−1 IM, single dose) was administered. Data were analyzed using t-tests, the Mann-Whitney test, and the Friedman test (P < 0.05). The pain scores did not differ between groups. However, postoperative supplemental analgesia was required by significantly more cats in the Control (5/10) compared with the Laser group (1/10) (P = 0.038). Laser acupuncture reduced postoperative analgesic requirements in cats undergoing ovariohysterectomy.
A most probable scan mode decision for H.264/AVC inter picture coding

Video coding standard H.264/AVC employs zig-zag scan and field scan to map transform coefficients from two dimensional matrix to one dimensional array. The zig-zag scan is used for transform coefficients in frame macroblocks (MBs), and the field scan is used in field MBs. This paper presents a most probable scan mode (MPSM) decision for H.264 inter picture coding. Besides the two scans, a horizontal scan is illustrated. For a 4×4 block, one out of the three scan modes is selected as the most probable one, and is used for the transform coefficient scan. Furthermore, an improved MPSM decision is discussed. Simulation results report that the proposed method yields an average of 1.15% bit rate reduction over the H.264 baseline profile.
Frame field generation through metric customization

This paper presents a new technique for frame field generation. As generic frame fields (with arbitrary anisotropy, orientation, and sizing) can be regarded as cross fields in a specific Riemannian metric, we tackle frame field design by first computing a discrete metric on the input surface that is compatible with a sparse or dense set of input constraints. The final frame field is then found by computing an optimal cross field in this customized metric. We propose frame field design constraints on alignment, size, and skewness at arbitrary locations on the mesh as well as along feature curves, offering much improved flexibility over previous approaches. We demonstrate the advantages of our frame field generation through the automatic quadrangulation of man-made and organic shapes with controllable anisotropy, robust handling of narrow surface strips, and precise feature alignment. We also extend our technique to the design of n-vector fields.
Decoding the ERD/ERS: influence of afferent input induced by a leg assistive robot

This paper investigates the influence of the leg afferent input, induced by a leg assistive robot, on the decoding performance of a BMI system. Specifically, it focuses on a decoder based on the event-related (de)synchronization (ERD/ERS) of the sensorimotor area. The EEG experiment, performed with healthy subjects, is structured as a 3 × 2 factorial design, consisting of two factors: “finger tapping task” and “leg condition. ” The former is divided into three levels (BMI classes), being left hand finger tapping, right hand finger tapping and no movement (Idle); while the latter is composed by two levels: leg perturbed (Pert) and leg not perturbed (NoPert). Specifically, the subjects' leg was periodically perturbed by an assistive robot in 5 out of 10 sessions of the experiment and not moved in the remaining sessions. The aim of this study is to verify that the decoding performance of the finger tapping task is comparable between the two conditions NoPert and Pert. Accordingly, a classifier is trained to output the class of the finger tapping, given as input the features associated with the ERD/ERS. Individually for each subject, the decoding performance is statistically compared between the NoPert and Pert conditions. Results show that the decoding performance is notably above chance, for all the subjects, under both conditions. Moreover, the statistical comparison do not highlight a significant difference between NoPert and Pert in any subject, which is confirmed by feature visualization.
Social Structure and Emotion

This paper explores the possibility of developing a general and formal social-action theory of labeling emotions. The theory is based upon the assumption that there is an underlying formal structural social-action system of expectations and sanctions that significantly influence how actors label their emotions. Some permutations of the four basic expectation-sanction states are elaborated, hypothetically labeled, and tested over a 14-year period. The “constructionist” view of the necessity of a cultural context in labeling emotions is challenged by removing the “moral” content from the survey instrument. The findings indicate that the formal model, devoid of content, is effective in differentiating emotion labels. The tests yielded promising results for developing a comprehensive and formal mapping of emotions. Taxonomical extrapolations of the theory are suggested and some further applications and needed research are discussed.
Viewpoint selection for visual failure detection

The visual difference between outcomes in many robotics tasks is often subtle, such as the tip of a screw being near a hole versus in the hole. Furthermore, these small differences are often only observable from certain viewpoints or may even require information from multiple viewpoints to fully verify. We introduce and compare three approaches to selecting viewpoints for verifying successful execution of tasks: (1) a random forest-based method that discovers highly informative fine-grained visual features, (2) SVM models trained on features extracted from pre-trained convolutional neural networks, and (3) an active, hybrid approach that uses the above methods for two-stage multi-viewpoint classification. These approaches are experimentally validated on an IKEA furniture assembly task and a quadrotor surveillance domain.
An Efficient Diagnosis Pattern Generation Procedure to Distinguish Stuck-at Faults and Bridging Faults

Fault Diagnosis is a critical process to identify the locations of physical defects in advanced integrated circuits. Current diagnosis tools often report multiple types of faults as defect candidates. Thus an efficient method to distinguish different types of faults is highly desired. Stuck-at and bridging faults are two most commonly used DC fault models during diagnosis. In this paper we present an efficient diagnosis pattern generation procedure to distinguish stuck-at faults and bridging faults. Two major techniques are proposed. The first one is a fault-inactivation method (FIM) that can quickly distinguish most fault pairs by inactivating one fault while detecting the other in each fault pair. The second one is a fault-types-transformation method (FTTM) that can transform the problem of distinguishing a stuck-at fault and a bridging fault into the problem of detecting a stuck-at fault. Both methods involve only one copy of the original circuit and require only an ordinary ATPG tool for stuck-at faults. Furthermore, both methods can deal with multiple fault pairs at a time and thus not only is the required CPU time small but also the dynamic test compaction capability of the ATPG tool can be utilized. Experiments on a large number of randomly selected fault pairs in ISCAS'89 and IWLS'05 benchmark circuits have been carried out. The results show that the FIM can distinguish about 91.9% of distinguishable fault pairs quickly and the FTTM can distinguish all other distinguishable fault pairs and identify all equivalent fault pairs. The average ratio of the number of diagnosis patterns over that of the test patterns for stuck-at faults is only 0.64. On average, one diagnosis pattern can distinguish 10.89 fault pairs.
The Value of the Hoover Commission Reports to the Educator

The Hoover Commission Reports were not written for the educator and his students. The audience was broader and the objective was immediate reform. Nevertheless, the educator must pause at this milepost and take stock. The reports are thrust upon him as inescapable materials for analysis in class and seminar rooms; they record in considerable measure the state of achievement in the development of administrative science; they challenge an examination now of the directions and scope of educational motive forces in the next phase of university education in public administration. Most teachers of public administration probably found the reports of the President's Committee on Administrative Management and of the Attorney General's Committee on Administrative Procedure to be very valuable aids in teaching. The publication of the Report with Special Studies and the Final Report provided a considerable body of material in convenient form for teacher and student use, and the over-all summary of the Committee on Administrative Management even provided material which could be used in introductory courses in American government. Also, these earlier reports dealt with problems at the growing points in the study of public administration and offered basic points of view around which discussion could be centered.
Quantitative Susceptibility Mapping at 3 T and 1.5 T: Evaluation of Consistency and Reproducibility

ObjectivesThe aim of this study was to assess the consistency and reproducibility of quantitative susceptibility mapping (QSM) at 3-T and 1.5-T magnetic resonance (MR) scanners. Materials and MethodsThis study was approved by institutional ethics committee, and written informed consent was obtained. Twenty-two healthy volunteers underwent 2 examinations on different days. Each examination consisted of MR imaging on both 3-T and 1.5-T MR scanners. The data from both scanners and examination days were obtained, and QSM was calculated with STI Suite using 2 different algorithms—harmonic phase removal using laplacian operator (HARPERELLA) and a sophisticated harmonic artifact reduction for phase data (SHARP) method with a variable radius of the spherical kernel at the brain boundary (V-SHARP). We evaluated consistency of QSM between 3 T and 1.5 T and the reproducibility between the first and second examinations using 2-phase processing methods (HARPERELLA and V-SHARP). ResultsSusceptibility values of regions of interests at 3 T were highly correlated with those at 1.5 T with good agreement (HARPERELLA, R2 = 0.838; V-SHARP, R2 = 0.898) (average difference, ±1.96 SD; HARPERELLA, −0.012 ± 0.046; V-SHARP, −0.002 ± 0.034). Reproducibility analysis demonstrated excellent correlation between the first and second examination at both 3 T and 1.5 T for both algorithms (HARPERELLA at 3 T, R2 = 0.921; 1.5 T, R2 = 0.891; V-SHARP at 3 T, R2 = 0.937; 1.5 T, R2 = 0.926). Bland-Altman analysis showed excellent reproducibility for HARPERELLA (3 T, −0.003 ± 0.032; 1.5 T, −0.003 ± 0.038) and V-SHARP (3 T, −0.003 ± 0.027; 1.5 T, −0.003 ± 0.029). Susceptibility values of these 2 algorithms were highly correlated with good agreement (3T, R2 = 0.961; 1.5 T, R2 = 0.931) (3 T, 0.009 ± 0.023; 1.5 T, −0.003 ± 0.049). ConclusionsQuantitative susceptibility mapping with HARPERELLA and V-SHARP demonstrated good reproducibility at 3 T and 1.5 T, and QSM with V-SHARP demonstrated good consistency at 3 T and 1.5 T.
Adaptive Data-Centric Clustering with Sensor Networks for Energy Efficient IoT Applications

A wireless sensor network (WSN) typically involves deploying multiple nodes in an area to measure environmental parameters. WSNs are getting enveloped within the realm of IoT which significantly increases their scale of deployment. The end-objective of deploying a sensor network is to get valuable data about a region irrespective of the physical configuration used for measurement. We propose an Adaptive Data-centric Clustering algorithm for Sensor networks (ADCS), a hierarchical algorithm where user-specific data requirements are factored into the clustering decisions. Specifically, similarity in parameter variations are used as a criteria for optimization. We have deployed an eKo-based sensor network in north-eastern India to measure environmental parameters as part of a precision agriculture application. Data from this network is used to develop models to rigorously compare the performance of three variants of ADCS: ADCS-DB, ADCS-KM and ADCS-AG and arrive at useful recommendations for deployment planning.
Some Evolutionary Economics of Family Partnerships

The article focuses on the economics of family partnerships. It states an allegory involving a prehistoric couple who split their responsibilities of gathering food and building a fire to create econometric models for family behavior. In theory, monogamous couples have exactly the same interest in their reproductive success, hence completely shared interest in their children. This is not the case in practice, as a variety of marital problems, divorce, and remarriage adversely affect the equation. The observed fact that an increase in a society's wealth tends to decrease family size runs counter to evolutionary biologic theory. No one theory in economics or biology has an adequate explanation for the reduction in family size as wealth increases. A variety of outside factors, notably the decline in child mortality and the change from an agricultural to an urban society, affect the models in both disciplines.
A distributed detection and isolation scheme for multiple sensor faults in interconnected nonlinear systems

This paper presents a distributed methodology for detecting and isolating multiple sensor faults in interconnected nonlinear systems. For each of the interconnected subsystems, a corresponding Local Sensor Fault Diagnosis (LSFD) agent is designed, which is allowed to exchange information with neighboring LSFD agents. The decisions of the LSFD agents are integrated and processed by a Global Sensor Fault Diagnosis (GSFD) agent in order to isolate multiple sensor faults propagating between neighboring LSFD agents through information exchange. The combined local and global isolation decision logic is designed based on diagnostic reasoning, taking into account the effects of sensor faults in the local sensor set and the transmitted faulty sensor information on the agents' decisions.
Production, Characterization, and Flocculation Mechanism of Cation Independent, pH Tolerant, and Thermally Stable Bioflocculant from Enterobacter sp. ETH-2

Synthetic high polymer flocculants, frequently utilized for flocculating efficiency and low cost, recently have been discovered as producing increased risk to human health and the environment. Development of a more efficient and environmentally sound alternative flocculant agent is investigated in this paper. Bioflocculants are produced by microorganisms and may exhibit a high rate of flocculation activity. The bioflocculant ETH-2, with high flocculating activity (2849 mg Kaolin particle/mg ETH-2), produced by strain Enterobacter sp. isolated from activated sludge, was systematically investigated with regard to its production, characterization, and flocculation mechanism. Analyses of microscopic observation, zeta potential and ETH-2 structure demonstrates the bridging mechanism, as opposed to charge neutralization, was responsible for flocculation of the ETH-2. ETH-2 retains high molecular weight (603 to 1820 kDa) and multi-functional groups (hydroxyl, amide and carboxyl) that contributed to flocculation. Polysaccharides mainly composed of mannose, glucose, and galactose, with a molar ratio of 1∶2.9∶9.8 were identified as the active constituents in bioflocculant. The structure of the long backbone with active sites of polysaccharides was determined as a primary basis for the high flocculation activity. Bioflocculant ETH-2 is cation independent, pH tolerant, and thermally stable, suggesting a potential fit for industrial application.
SAP: Similarity-aware partitioning for efficient cloud storage

Given a set of files that show a certain degree of similarity, we consider a novel problem of deduplicating them (eliminating redundant chunks) across a set of distributed servers in a manner that is: (i) space-efficient: the total space needed to deduplicate and store the files is minimized and, (ii) access-efficient: each file can be accessed by communicating with a bounded number of servers, thereby minimizing network-access times in congested data center networks. A space-optimal solution in which we first deduplicate all the files and then distribute them across the servers (referred to as chunk-distribution), may require communication with many servers to access each file. On the other hand, an access-efficient solution in which we randomly partition the files cross the servers, and then store their unique chunks on each server may not exploit the similarities across files to reduce the space overhead. In this paper, we first show that finding an access-efficient, space optimal solution is an NP-Hard problem. Following this, we present the similarity-aware-partitioning (SAP) algorithms that find access-efficient solutions within polynomial time complexity and guarantees bounded space overhead for arbitrary files. Our experimental verification on files from Dropbox and CNN confirm that the SAP technique is much more space-efficient than random partitioning, while maintaining compression ratio close to the chunk-distribution solution.