Information Sharing and Interoperability in Law Enforcement: An Investigation of Federal Criminal Justice Information Systems Use by State/Local Law Enforcement Organizations

This thesis investigates the frequency of use and perceptions of usefulness of federal criminal justice information systems among state and local law enforcement personnel and certain IS environmental factors that affect usage. The study is predicated by a demonstrated need for increased information sharing, interoperability, and collaboration among the three tiers of law enforcement as public safety threats within U.S. borders increase in complexity; e.g., the Murrah Federal Building bombing, Columbine High School shooting, 9/11 terrorist attacks, and D.C. sniper case. The results of this research indicate high usage and perceived usefulness of the National Crime Information Center Network (NCIC Net), National Law Enforcement Telecommunications System (NLETS), Uniform Crime Reporting/National Incident Based Reporting System (UCR/NIBRS), National Instant Criminal Background Check System (NICS), and federal LE websites. The results also indicated that the IS environmental factors information quality and trust influenced the usage and perceived usefulness of federal criminal justice information systems

Synthesis, Infra-red, Raman, NMR and structural characterization by X-ray Diffraction of [C12H17N2]2CdCl4 and [C6H10N2]2Cd3Cl10 compounds

The synthesis, infra-red, Raman and NMR spectra and crystal structure of 2, 4, 4- trimethyl-4, 5- dihydro-3H-benzo[b] [1, 4] diazepin-1-ium tetrachlorocadmate, [C12H17N2]2CdCl4 and benzene-1,2-diaminium decachlorotricadmate(II) [C6H10N2]2Cd3Cl10 are reported. The [C12H17N2]2CdCl4 compound crystallizes in the triclinic system (P-1 space group) with Z = 2 and the following unit cell dimensions: a = 9.6653(8) angstrom, b = 9.9081(9) angstrom, c = 15.3737(2) angstrom, alpha = 79.486(1)degrees, beta = 88.610(8)degrees and gamma = 77.550(7)degrees. The structure was solved by using 4439 independent reflections down to R value of 0.029. In crystal structure, the tetrachlorocadmiate anion is connected to two organic cations through N-H...Cl hydrogen bonds and Van Der Waals interaction as to build cation-anion-cation cohesion. The [C6H10N2]2Cd3Cl10 crystallizes in the triclinic system (P-1 space group). The unit cell dimensions are a = 6.826 (5)angstrom, b = 9.861 (7)angstrom, c = 10.344 (3)angstrom, alpha = 103.50 (1)degrees, beta = 96.34 (4)degrees and gamma = 109.45 (3)degrees, Z=2. The final R value is 0.053 (Rw=0.128). Its crystal structure consists of organic cations and polymeric chains of [Cd3Cl10]4- anions running along the [011] direction, In The [C6H10N2]2Cd3Cl10 compounds hydrogen bond interactions between the inorganic chains and the organic cations, contribute to the crystal packing. PACS Codes: 61.10.Nz, 61.18.Fs, 78.30.-jComment: 19 pages, 10 figure

A thorough anion-π interaction study in biomolecules:On the importance of cooperativity effects

Noncovalent interactions have a constitutive role in the science of intermolecular relationships, particularly those involving aromatic rings such as π-π and cation-π. In recent years, anion-π contact has also been recognized as a noncovalent bonding interaction with important implications in chemical processes. Yet, its involvement in biological processes has been scarcely reported. Herein we present a large-scale PDB analysis of the occurrence of anion-π interactions in proteins and nucleic acids. In addition we have gone a step further by considering the existence of cooperativity effects through the inclusion of a second noncovalent interaction, i.e. π-stacking, T-shaped, or cation-π interactions to form anion-π-π and anion-π-cation triads. The statistical analysis of the thousands of identified interactions reveals striking selectivities and subtle cooperativity effects among the anions, π-systems, and cations in a biological context. The reported results stress the importance of anion-π interactions and the cooperativity that arises from ternary contacts in key biological processes, such as protein folding and function and nucleic acids-protein and protein-protein recognition. We include examples of anion-π interactions and triads putatively involved in enzymatic catalysis, epigenetic gene regulation, antigen-antibody recognition, and protein dimerization

Consequence of one-electron oxidation and one-electron reduction for aniline

Quantum-chemical calculations were performed for all possible isomers of neutral aniline and its redox forms, and intramolecular proton-transfer (prototropy) accompanied by π-electron delocalization was analyzed. One-electron oxidation (PhNH2 – e → [PhNH2]+•) has no important effect on tautomeric preferences. The enamine tautomer is preferred for oxidized aniline similarly as for the neutral molecule. Dramatical changes take place when proceeding from neutral to reduced aniline. One-electron reduction (PhNH2 + e → [PhNH2]-•) favors the imine tautomer. Independently on the state of oxidation, π- and n-electrons are more delocalized for the enamine than imine tautomers. The change of the tautomeric preferences for reduced aniline may partially explain the origin of the CH tautomers for reduced nucleobases (cytosine, adenine, and guanine)

Density functional theory study of the multimode Jahn-Teller effect – ground state distortion of benzene cation

The multideterminental-DFT approach performed to analyze Jahn-Teller (JT) active molecules is described. Extension of this method for the analysis of the adiabatic potential energy surfaces and the multimode JT effect is presented. Conceptually a simple model, based on the analogy between the JT distortion and reaction coordinates gives further information about microscopic origin of the JT effect. Within the harmonic approximation the JT distortion can be expressed as a linear combination of all totally symmetric normal modes in the low symmetry minimum energy conformation, which allows calculating the Intrinsic Distortion Path, IDP, exactly from the high symmetry nuclear configuration to the low symmetry energy minimum. It is possible to quantify the contribution of different normal modes to the distortion, their energy contribution to the total stabilization energy and how their contribution changes along the IDP. It is noteworthy that the results obtained by both multideterminental-DFT and IDP methods for different classes of JT active molecules are consistent and in agreement with available theoretical and experimental values. As an example, detailed description of the ground state distortion of benzene cation is given

Gastrokine-1, an anti-amyloidogenic protein secreted by the stomach, regulates diet-induced obesity

Obesity and its sequelae have a major impact on human health. The stomach contributes to obesity in ways that extend beyond its role in digestion, including through effects on the microbiome. Gastrokine-1 (GKN1) is an anti-amyloidogenic protein abundantly and specifically secreted into the stomach lumen. We examined whether GKN1 plays a role in the development of obesity and regulation of the gut microbiome. Gkn1−/− mice were resistant to diet-induced obesity and hepatic steatosis (high fat diet (HFD) fat mass (g) = 10.4 ± 3.0 (WT) versus 2.9 ± 2.3 (Gkn1−/−) p < 0.005; HFD liver mass (g) = 1.3 ± 0.11 (WT) versus 1.1 ± 0.07 (Gkn1−/−) p < 0.05). Gkn1−/− mice also exhibited increased expression of the lipid-regulating hormone ANGPTL4 in the small bowel. The microbiome of Gkn1−/− mice exhibited reduced populations of microbes implicated in obesity, namely Firmicutes of the class Erysipelotrichia. Altered metabolism consistent with use of fat as an energy source was evident in Gkn1−/− mice during the sleep period. GKN1 may contribute to the effects of the stomach on the microbiome and obesity. Inhibition of GKN1 may be a means to prevent obesity

Making effective use of healthcare data using data-to-text technology

Healthcare organizations are in a continuous effort to improve health outcomes, reduce costs and enhance patient experience of care. Data is essential to measure and help achieving these improvements in healthcare delivery. Consequently, a data influx from various clinical, financial and operational sources is now overtaking healthcare organizations and their patients. The effective use of this data, however, is a major challenge. Clearly, text is an important medium to make data accessible. Financial reports are produced to assess healthcare organizations on some key performance indicators to steer their healthcare delivery. Similarly, at a clinical level, data on patient status is conveyed by means of textual descriptions to facilitate patient review, shift handover and care transitions. Likewise, patients are informed about data on their health status and treatments via text, in the form of reports or via ehealth platforms by their doctors. Unfortunately, such text is the outcome of a highly labour-intensive process if it is done by healthcare professionals. It is also prone to incompleteness, subjectivity and hard to scale up to different domains, wider audiences and varying communication purposes. Data-to-text is a recent breakthrough technology in artificial intelligence which automatically generates natural language in the form of text or speech from data. This chapter provides a survey of data-to-text technology, with a focus on how it can be deployed in a healthcare setting. It will (1) give an up-to-date synthesis of data-to-text approaches, (2) give a categorized overview of use cases in healthcare, (3) seek to make a strong case for evaluating and implementing data-to-text in a healthcare setting, and (4) highlight recent research challenges.Comment: 27 pages, 2 figures, book chapte

Theiler's Murine Encephalomyelitis Virus as a Vaccine Candidate for Immunotherapy

The induction of sterilizing T-cell responses to tumors is a major goal in the development of T-cell vaccines for treating cancer. Although specific components of anti-viral CD8+ immunity are well characterized, we still lack the ability to mimic viral CD8+ T-cell responses in therapeutic settings for treating cancers. Infection with the picornavirus Theiler's murine encephalomyelitis virus (TMEV) induces a strong sterilizing CD8+ T-cell response. In the absence of sterilizing immunity, the virus causes a persistent infection. We capitalized on the ability of TMEV to induce strong cellular immunity even under conditions of immune deficiency by modifying the virus to evaluate its potential as a T-cell vaccine. The introduction of defined CD8+ T-cell epitopes into the leader sequence of the TMEV genome generates an attenuated vaccine strain that can efficiently drive CD8+ T-cell responses to the targeted antigen. This virus activates T-cells in a manner that is capable of inducing targeted tissue damage and glucose dysregulation in an adoptive T-cell transfer model of diabetes mellitus. As a therapeutic vaccine for the treatment of established melanoma, epitope-modified TMEV can induce strong cytotoxic T-cell responses and promote infiltration of the T-cells into established tumors, ultimately leading to a delay in tumor growth and improved survival of vaccinated animals. We propose that epitope-modified TMEV is an excellent candidate for further development as a human T-cell vaccine for use in immunotherapy

A Biological Global Positioning System: Considerations for Tracking Stem Cell Behaviors in the Whole Body

Many recent research studies have proposed stem cell therapy as a treatment for cancer, spinal cord injuries, brain damage, cardiovascular disease, and other conditions. Some of these experimental therapies have been tested in small animals and, in rare cases, in humans. Medical researchers anticipate extensive clinical applications of stem cell therapy in the future. The lack of basic knowledge concerning basic stem cell biology-survival, migration, differentiation, integration in a real time manner when transplanted into damaged CNS remains an absolute bottleneck for attempt to design stem cell therapies for CNS diseases. A major challenge to the development of clinical applied stem cell therapy in medical practice remains the lack of efficient stem cell tracking methods. As a result, the fate of the vast majority of stem cells transplanted in the human central nervous system (CNS), particularly in the detrimental effects, remains unknown. The paucity of knowledge concerning basic stem cell biology—survival, migration, differentiation, integration in real-time when transplanted into damaged CNS remains a bottleneck in the attempt to design stem cell therapies for CNS diseases. Even though excellent histological techniques remain as the gold standard, no good in vivo techniques are currently available to assess the transplanted graft for migration, differentiation, or survival. To address these issues, herein we propose strategies to investigate the lineage fate determination of derived human embryonic stem cells (hESC) transplanted in vivo into the CNS. Here, we describe a comprehensive biological Global Positioning System (bGPS) to track transplanted stem cells. But, first, we review, four currently used standard methods for tracking stem cells in vivo: magnetic resonance imaging (MRI), bioluminescence imaging (BLI), positron emission tomography (PET) imaging and fluorescence imaging (FLI) with quantum dots. We summarize these modalities and propose criteria that can be employed to rank the practical usefulness for specific applications. Based on the results of this review, we argue that additional qualities are still needed to advance these modalities toward clinical applications. We then discuss an ideal procedure for labeling and tracking stem cells in vivo, finally, we present a novel imaging system based on our experiments

A new benchmark dataset with production methodology for short text semantic similarity algorithms

This research presents a new benchmark dataset for evaluating Short Text Semantic Similarity (STSS) measurement algorithms and the methodology used for its creation. The power of the dataset is evaluated by using it to compare two established algorithms, STASIS and Latent Semantic Analysis. This dataset focuses on measures for use in Conversational Agents; other potential applications include email processing and data mining of social networks. Such applications involve integrating the STSS algorithm in a complex system, but STSS algorithms must be evaluated in their own right and compared with others for their effectiveness before systems integration. Semantic similarity is an artifact of human perception; therefore its evaluation is inherently empirical and requires benchmark datasets derived from human similarity ratings. The new dataset of 64 sentence pairs, STSS-131, has been designed to meet these requirements drawing on a range of resources from traditional grammar to cognitive neuroscience. The human ratings are obtained from a set of trials using new and improved experimental methods, with validated measures and statistics. The results illustrate the increased challenge and the potential longevity of the STSS-131 dataset as the Gold Standard for future STSS algorithm evaluation. © 2013 ACM 1550-4875/2013/12-ART17 15.00