Robust-diagnostic regression : a prelude for inducing reliable knowledge from regression

Regression lies heart in statistics, it is the one of the most important branch of multivariate techniques available for extracting knowledge in almost every field of study and research. Nowadays, it has drawn a huge interest to perform the tasks with different fields like machine learning, pattern recognition and data mining. Investigating outlier (exceptional) is a century long problem to the data analyst and researchers. Blind application of data could have dangerous consequences and leading to discovery of meaningless patterns and carrying to the imperfect knowledge. As a result of digital revolution and the growth of the Internet and Intranet data continues to be accumulated at an exponential rate and thereby importance of detecting outliers and study their costs and benefits as a tool for reliable knowledge discovery claims perfect attention. Investigating outliers in regression has been paid great value for the last few decades within two frames of thoughts in the name of robust regression and regression diagnostics. Robust regression first wants to fit a regression to the majority of the data and then to discover outliers as those points that possess large residuals from the robust output whereas in regression diagnostics one first finds the outliers, delete/correct them and then fit the regular data by classical (usual) methods. At the beginning there seems to be much confusion but now the researchers reach to the consensus, robustness and diagnostics are two complementary approaches to the analysis of data and any one is not good enough. In this chapter, we discuss both of them under the unique spectrum of regression diagnostics. Chapter expresses the necessity and views of regression diagnostics as well as presents several contemporary methods through numerical examples in linear regression within each aforesaid category together with current challenges and possible future research directions. Our aim is to make the chapter self-explained maintaining its general accessibility.

Spectroscopic techniques

Spectroscopic techniques are widely used in forensic laboratories for quantitative and qualitative analysis. This artictle provides an overview of the spectroscopic techniques most commonly encountered in forensic laboratories. Infrared spectroscopy, Raman spectroscopy, X-ray fluorescence, scanning electron microscopy energy dispersive X-ray spectroscopy, and nuclear magnetic resonance spectroscopy are used mainly for identification or characterization of substances. Visible and ultraviolet spectroscopy, atomic absorption spectroscopy and atomic emission spectroscopy are used mainly for measurement of substances or elements. Some techniques can be used for both identification and measurement. Related techniques such as molecular fluorescence, chemiluminescence and synchrotron techniques are also discussed.

Molecular sex-typing in shorebirds: a review of an essential method for research in evolution, ecology and conservation

Knowing the correct sex of individuals is essential both for research in evolutionary ecology and for practical conservation. Recent molecular advances have produced cheap, quick and reliable methods for sexing birds including chicks, juveniles, immatures and adults. Shorebird researchers have not yet fully utilised these advances. Here we provide an overview of work in this area to date with two objectives: (i) to review the major applications of molecular sexing and findings of shorebird research so far, and (ii) to provide an essential guide on how to carry out molecular sexing using current methods whilst avoiding methodological pitfalls. We encourage shorebird researchers to make better use of molecular sex-typing techniques in studies of conservation, migration, foraging ecology and breeding behaviour.

Simultaneous polymerization and crosslinking for the synthesis of molecular-level graphene oxide-polyacryl amide-CeOx composites

Synthesis of molecular-level multiple-component composites are particularly challenging due to the lack of direct bonding among different components. In this study, molecular-level graphene oxide (GO)-polyacryl amide (PAM)-CeOx composites were successfully synthesized, using the simultaneous polymerization and crosslinking strategy. Attenuated total reflection Fourier transform infrared (ATR-FTIR) and nuclear magnetic resonance (NMR) techniques confirmed that polyacryl amide (PAM) chains were successfully grafted onto the surface of GO. X-ray photoelectron spectroscopic (XPS) and X-ray diffraction (XRD) analyses further revealed the characteristic signals of cerium elements and CeO2 phase respectively. Scanning electron microscopy (SEM) showed that the surface morphology of the GO-PAM-CeOx composites was substantially thicker and rougher than those of the original GO. Further exploration of the reaction mechanism clearly demonstrate the existence of strong chelating interaction among PAM chains and Ce(IV) ions. In particular, the polymerization of acryl amide monomers and the crosslinking reaction between PAM and Ce(IV) or Ce(III) ions were realized simultaneously, leading to the final formation of molecular-level GO-PAM-CeOx composites. Moreover, the as-synthesized GO-PAM-CeOx composites were capable of effectively decomposing Rhodamine B under simulated sunlight, making it a potential candidate as a new photo catalyst. To sum up, this report demonstrates the potential utility of simultaneous polymerization and crosslinking method for the synthesis of other multiple-component composites at molecular-level.

Microfluidic platforms for biomarker analysis

Biomarkers have been described as characteristics, most often molecular, that provide information about biological states, whether normal, pathological, or therapeutically modified. They hold great potential to assist diagnosis and prognosis, monitor disease, and assess therapeutic effectiveness. While a few biomarkers are routinely utilised clinically, these only reflect a very small percentage of all biomarkers discovered. Numerous factors contribute to the slow uptake of these new biomarkers, with challenges faced throughout the biomarker development pipeline. Microfluidics offers two important opportunities to the field of biomarkers: firstly, it can address some of these developmental obstacles, and secondly, it can provide the precise and complex platform required to bridge the gap between biomarker research and the biomarker-based analytical device market. Indeed, adoption of microfluidics has provided a new avenue for advancement, promoting clinical utilisation of both biomarkers and their analytical platforms. This review will discuss biomarkers and outline microfluidic platforms developed for biomarker analysis.

Distinct kinetics of molecular gelation in a confined space and its relation to the structure and property of thin gel films

Thin films of molecular gels formed in a confined space have potential applications in transdermal delivery, artificial skin, molecular electronics, etc. The microstructures and properties of thin gel films can be significantly different from those of their bulk counterparts. However, so far a comprehensive understanding of the effects of spatial confinement on the molecular gelation kinetics, fiber network structure and related mechanical properties is still lacking. In this work, using rheological techniques, we investigated the effect of one-dimensional confinement on the formation kinetics of fiber networks in the molecular gelation process. Fractal analyses of the kinetic information in terms of an extended Dickinson model enabled us to describe quantitatively the distinct kinetic signature of molecular gelation. The structural features derived from gelation kinetics support well the fractal patterns of the fiber networks acquired by optical and electron microscopy. With the kinetics-structure correlation, we can gain an in-depth understanding of the confinement-induced differences in the structure and consequently the mechanical properties of a model molecular gelling system. Particularly, the confinement induced structural transition, from a three-dimensional, dense and compact spherulitic network composed of highly branched fibers to a quasi-two-dimensional sparse spherulitic network composed of less branched fibers and entangled fibrils at the boundary areas, renders a gel film to become less stiff but more ductile. Our study suggests here a new strategy of engineering the fiber network microstructure to achieve functional gel films with unusual but useful properties.

Molecular targets in arthritis and recent trends in nanotherapy

Due to its severity and increasing epidemiology, arthritis needs no description. There are various forms of arthritis most of which are disabling, very painful, and common. In spite of breakthroughs in the field of drug discovery, there is no cure for arthritis that can eliminate the disease permanently and ease the pain. The present review focuses on some of the most successful drugs in arthritis therapy and their side effects. Potential new targets in arthritis therapy such as interleukin-1β, interleukin-17A, tumor necrosis factor alpha, osteopontin, and several others have been discussed here, which can lead to refinement of current therapeutic modalities. Mechanisms for different forms of arthritis have been discussed along with the molecules that act as potential biomarkers for arthritis. Due to the difficulty in monitoring the disease progression to detect the advanced manifestations of the diseases, drug-induced cytotoxicity, and problems with drug delivery; nanoparticle therapy has gained the attention of the researchers. The unique properties of nanoparticles make them highly attractive for the design of novel therapeutics or diagnostic agents for arthritis. The review also focuses on the recent trends in nanoformulation development used for arthritis therapy. This review is, therefore, important because it describes the relevance and need for more arthritis research, it brings forth a critical discussion of successful drugs in arthritis and analyses the key molecular targets. The review also identifies several knowledge gaps in the published research so far along with the proposal of new ideas and future directions in arthritis therapy.

Solid-state NMR as a probe of anion binding: molecular dynamics and associations in a [5]polynorbornane bisurea host complexed with terephthalate

A range of solid-state NMR techniques is used to characterise a molecular host:guest complex consisting of a [5]polynorbornane bisurea host binding a terephthalate dianion guest. Detailed information is obtained on the molecular dynamics and associations from the point of view of both the host and guest molecules. The formation of the complex in the solid state is confirmed using (1)H 2D exchange NMR, and the 180° flipping of the (2)H-labelled terephthalate guest and its eventual expulsion from the complex at elevated temperatures are quantified using variable-temperature (2)H spin-echo experiments. Two-dimensional (1)H-(13)C HETCOR spectra obtained under fast magic angle spinning conditions (60 kHz) show a high resolution despite the poor crystallinity of the solid complex, and clearly reveal changes in the rigidity of the host molecule when complexed. Short-range intra- and intermolecular (1)H-(1)H proximities are also detected using 2D SQ-DQ correlation methods, providing insight into the molecular packing in the solid phase.