Atomic Spectroscopy

Atomic spectroscopy includes a number of analytical techniques used to determine the elemental composition of a sample (it can be gas, liquid, or solid) by observing its electromagnetic spectrum or its mass spectrum. Element concentrations of a millionth (ppm) or one billionth part (ppb) of the sample can be detected. There are different variations of atomic spectroscopy, emission, absorption, fluorescence, and mass spectroscopy. Determination of an appropriate technique requires a basic understanding of each technique since each has its individual strengths and limitations. This chapter is designed to provide a basic overview to the atomic spectroscopy techniques and how can you select the one that best suits our analytical problems

Frauen als Teil der Informatik - Die Analyse der Position von Frauen im Vergleich zu MINT

Informatik ist eine männerdominierte Wissenschaft, welches sich an den Männeranteilen sowohl im Studium als auch in der Berufswelt bemerkbar macht. Aus diesen und weiteren Gründen trauen sich viele Frauen nicht in das Gebiet Informatik einzusteigen. Der niedrige Frauenanteil ist eine Lücke für die Wissenschaft. Die Qualifikationen von Frauen werden benötigt, um neue Sichtweisen zu bekommen und andere Arbeitsweisen kreieren zu können. Damit die Frauenquote in der Informatik steigt, müssen die Ursachen analysiert und dagegen entsprechende Maßnahmen getroffen werden. Die vielfältigen Seiten des Gebietes müssen enthüllt und mit anderen Wissenschaften verknüpft werden, so dass Frauen auch eigene Interessen darin finden können.Informatics is a male-dominated science, which makes itself felt on the men share as well in the education as in the professional world. For these and other reasons many women don’t dare to get into the area informatics. The low share of women is a gap for this science. The qualifications of women are required to get new perspectives and create other work methods. To increase the proportion of women in informatics, the causes must be analyzed and against that appropriate measures must be taken. The diverse sides of the area must be revealed and be linked with other sciences, so that women can also find their own interests in it

Tuning of the electronic and optical properties of single layer black phosphorus by strain

Using first principles calculations we showed that the electronic and optical properties of single layer black phosphorus (BP) depend strongly on the applied strain. Due to the strong anisotropic atomic structure of BP, its electronic conductivity and optical response are sensitive to the magnitude and the orientation of the applied strain. We found that the inclusion of many body effects is essential for the correct description of the electronic properties of monolayer BP; for example while the electronic gap of strainless BP is found to be 0.90 eV by using semilocal functionals, it becomes 2.31 eV when many-body effects are taken into account within the G0W0 scheme. Applied tensile strain was shown to significantly enhances electron transport along zigzag direction of BP. Furthermore, biaxial strain is able to tune the optical band gap of monolayer BP from 0.38 eV (at -8% strain) to 2.07 eV (at 5.5%). The exciton binding energy is also sensitive to the magnitude of the applied strain. It is found to be 0.40 eV for compressive biaxial strain of -8%, and it becomes 0.83 eV for tensile strain of 4%. Our calculations demonstrate that the optical response of BP can be significantly tuned using strain engineering which appears as a promising way to design novel photovoltaic devices that capture a broad range of solar spectrum

Spectral Analysis Methods for Spike-Wave Discharges in Rats with Genetic Absence Epilepsy

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Design of a Single AAV Vector for Coexpression of TH and GCH1 to Establish Continuous DOPA Synthesis in a Rat Model of Parkinson's Disease.

Preclinical efficacy of continuous delivery of 3,4-dihydroxyphenylalanine (DOPA) with adeno-associated viral (AAV) vectors has recently been documented in animal models of Parkinson's disease (PD). So far, all studies have utilized a mix of two monocistronic vectors expressing either of the two genes, tyrosine hydroxylase (TH) and GTP cyclohydrolase-1 (GCH1), needed for DOPA production. Here, we present a novel vector design that enables efficient DOPA production from a single AAV vector in rats with complete unilateral dopamine (DA) lesions. Functional efficacy was assessed with drug-induced and spontaneous motor behavioral tests where vector-treated animals showed near complete and stable recovery within 1 month. Recovery of motor function was associated with restoration of extracellular DA levels as assessed by online microdialysis. Histological analysis showed robust transgene expression not only in the striatum but also in overlying cortical areas. In globus pallidus, we noted loss of NeuN staining, which might be due to different sensitivity in neuronal populations to transgene expression. Taken together, we present a single AAV vector design that result in efficient DOPA production and wide-spread transduction. This is a favorable starting point for continued translation toward a therapeutic application, although future studies need to carefully review target region, vector spread and dilution with this approach

Static malware detection Using Stacked BiLSTM and GPT-2

In recent years, cyber threats and malicious software attacks have been escalated on various platforms. Therefore, it has become essential to develop automated machine learning methods for defending against malware. In the present study, we propose stacked bidirectional long short-term memory (Stacked BiLSTM) and generative pre-trained transformer based (GPT-2) deep learning language models for detecting malicious code. We developed language models using assembly instructions extracted from .text sections of malicious and benign Portable Executable (PE) files. We treated each instruction as a sentence and each .text section as a document. We also labeled each sentence and document as benign or malicious, according to the file source. We created three datasets from those sentences and documents. The first dataset, composed of documents, was fed into a Document Level Analysis Model (DLAM) based on Stacked BiLSTM. The second dataset, composed of sentences, was used in Sentence Level Analysis Models (SLAMs) based on Stacked BiLSTM and DistilBERT, Domain Specific Language Model GPT-2 (DSLM-GPT2), and General Language Model GPT-2 (GLM-GPT2). Lastly, we merged all assembly instructions without labels for creating the third dataset; then we fed a custom pre-trained model with it. We then compared malware detection performances. The results showed that the pre-trained model improved the DSLM-GPT2 and GLM-GPT2 detection performance. The experiments showed that the DLAM, the SLAM based on DistilBERT, the DSLM-GPT2, and the GLM-GPT2 achieved 98.3%, 70.4%, 86.0%, and 76.2% F1 scores, respectively