Enhancing the selectivity of frequency selective surfaces for terahertz sensing applications

This paper introduces a new technique for enhancing the selectivity (or the quality factor, Q-factor) of frequency selective surfaces (FSS) for sensing applications. The proposed FSS functions as a free-space bandpass resonator, designed to sense the changing dielectric properties of minute amount of materials loaded on the FSS. The Q-enhancement technique is mainly based on two concepts; enhancing the field concentration in a given area and introducing transmission zeros in the FSS response. Two designs based on a modified complementary split-ring resonator (CSRR) at 300 GHz have been proposed. The first one is composed of complementary triple-split ring resonators. The splits divided the structure into arcs of different lengths. As a result, the transmission zero is obtained in the passband due to a destructive coupling. This produces a resonance Q-factor of 41. By controlling the orientation of the three splits, higher Q-factor of 84 is attainable. The second structure is designed using concentric triple-split rings. The added electromagnetic coupling between the concentric rings makes the transmission response steeper as compared with the single triple-split ring, and the quality factor increases from 41 to 90. By reducing the inter-spacing distance by three times, the Q-factor can be further increased to 256. The parameter studies of the FSS structures based on full-wave simulations have been presented

The quinoxaline di-N-oxide DCQ blocks breast cancer metastasis in vitro and in vivo by targeting the hypoxia inducible factor-1 pathway

BACKGROUND: Although tumor hypoxia poses challenges against conventional cancer treatments, it provides a therapeutic target for hypoxia-activated drugs. Here, we studied the effect of the hypoxia-activated synthetic quinoxaline di-N-oxide DCQ against breast cancer metastasis and identified the underlying mechanisms. METHODS: The human breast cancer cell lines MCF-7 (p53 wildtype) and MDA-MB-231 (p53 mutant) were treated with DCQ under normoxia or hypoxia. Drug toxicity on non-cancerous MCF-10A breast cells was also determined. In vitro cellular responses were investigated by flow cytometry, transfection, western blotting, ELISA and migration assays. The anti-metastatic effect of DCQ was validated in the MDA-MB-231 xenograft mouse model. RESULTS: DCQ selectively induced apoptosis in both human breast cancer cells preferentially under hypoxia without affecting the viability of non-cancerous MCF-10A. Cancer cell death was associated with an increase in reactive oxygen species (ROS) independently of p53 and was inhibited by antioxidants. DCQ-induced ROS was associated with DNA damage, the downregulation of hypoxia inducible factor-1 alpha (HIF-1α), and inhibition of vascular endothelial growth factor (VEGF) secretion. In MCF-7, HIF-1α inhibition was partially via p53-activation and was accompanied by a decrease in p-mTOR protein, suggesting interference with HIF-1α translation. In MDA-MB-231, DCQ reduced HIF-1α through proteasomal-dependent degradation mechanisms. HIF-1α inhibition by DCQ blocked VEGF secretion and invasion in MCF-7 and led to the inhibition of TWIST in MDA-MB-231. Consistently, DCQ exhibited robust antitumor activity in MDA-MB-231 breast cancer mouse xenografts, enhanced animal survival, and reduced metastatic dissemination to lungs and liver. CONCLUSION: DCQ is the first hypoxia-activated drug showing anti-metastatic effects against breast cancer, suggesting its potential use for breast cancer therapy

Influence of short- and long-term administration of Melengestrol acetate on estrus activity and reproductive performance of nulliparous Barki ewes

In Egypt, research focusing on estrous synchronization in small ruminants based on Melengestrol acetate (MGA) supplementation, particularly in nulliparous ewes, is still lacking. The present work aimed to evaluate effect of long-term and short-term administration of melengestrol acetate (MGA) treatments on estrus synchronization and reproductive performance of nulliparous Barki Ewes. This study was performed in Siwa Oasis Research Station (Tegzerty Experimental Farm for animal production), belonged to Desert Research Center, Egypt. Forty five nulliparous Barki ewes with age ranging from 15.5 to 16.5 months, and 38 ± 0.23 kg average live body weight were assigned to one of three groups: (1) control (C, n = 15); (2) long-term treatment with MGA (n = 15, 0.22 mg/ewe/d for 14 days) and (3) short-term treatment with MGA (n = 15, 0.22 mg/ewe/d for 7 days). At the end of MGA treatment (14 or 7 d) all treated ewes were injected by 600 IU PMSG intramuscularly. The results showed that, ewes treated with MGA exhibited highest (

Small molecule tyrosine kinase inhibitors in pancreatic cancer

Pancreatic cancer has proven to be chemo-resistant, with gemcitabine being the only cytotoxic agent approved for advanced pancreatic cancer since 1996. Tyrosine kinase inhibitors represent a newer generation of chemotherapeutic agents targeting specific tumor pathways associated with carcinogenesis including cell cycle control, signal transduction, apoptosis and angiogenesis. These agents present a more selective way of treating pancreatic cancer. Erlotinib is the prototype of the tyrosine kinase inhibitors with proven efficacy in advanced pancreatic cancer and has been recently approved in that setting. Multiple other tyrosine kinase inhibitors targeting the VEGFR, PDGFR, and Src kinases are in various phases of clinical trials testing. The preliminary results of these trials have been disappointing. Current challenges in pancreatic cancer clinical trials testing include improving patient selection, identifying effective combinations, improving the predictive value of current preclinical models and better study designs. This review summarizes the present clinical development of tyrosine kinase inhibitors in pancreatic cancer and strategies for future drug development

An Explicative and Predictive Study of Employee Attrition using Tree-based Models

We develop tree-based models to estimate the probability of an employee leaving a firm during a job transition from a dataset of anonymously submitted resumes through Glassdoor’s online portal. Dataset construction and summary statistics are first summarized followed by a more in depth examination through four exploratory studies. Insights provided by these studies are then used to engineer features that serve as input into subsequent attrition related predictive models. We finally perform a thorough search through several dozen binary classification techniques in the cases of an original and extended feature set. We find tree-based methods including random forests and light gradient boosted trees provide the overall strongest predictive performance. Finally, we summarize ROC curves for several such models and describe future potential research directions

Field Disruption Energy Harvester Design and Modeling: A Novel Approach in Electromagnetic Vibration Energy Harvesting

The demand for sustainable and non-traditional sources of energy increases every day to power up different electronic equipment whether it's portable low-power devices, non-accessible sensors, wearable electronics, implantable medical devices, and even for big scale applications that can contribute to the energy demand on a public level. Energy harvesting from vibrations offers an ideal source of energy, since it's renewable and prevailing, where kinetic energy that can be harvested is abundant in nature. \newline In this proposal, a novel electromagnetic transduction mechanism is introduced that can be used in harvesting low-frequency vibrations below 10 Hz, which makes it suitable to harvest motion from human locomotion, moving vehicles, and structures like buildings, bridges and streets. The transduction mechanism developed induces a current in a coil by disrupting the electromagnetic field in the vicinity of a stationary coil wound around a hollow track (tube) made of non-conducting or conducting (copper) material, where a ball made of ferromagnetic material is moving freely along the track cutting the field lines and induces current in the coil. Prototypes embodying the harvesting mechanism were fabricated and tested to identify the different system parameters, frequency-responses and characterize the harvester in order to derive a representative mathematical model. The performance of the energy harvester was measured and characterized in terms of output power, power density and tunability. Where the prototypes fabricated demonstrated a capability to harvest energy at low-frequencies in the range of 6.54-12.72 Hz , with a 3 dB harvesting bandwidth ranging between 1.32 Hz to 5.8 Hz, and generated output power up to 154 micro-Watt. The proposed transduction mechanism demonstrated a strong flexibility that allows tuning the center frequency magnetically, without the need to modify the mechanical design, in order to take advantage of this feature, an intelligent fuzzy tuner design is proposed, supported with simulation results that show the potential of adaptive control of center frequency to increase the generated output power. \newline This abstract proposes a future plan for the development of the intelligent fuzzy tuner hardware and it's validation to increase the generated output power and power density at low frequencies while reducing the need for any external interference in the harvester's operation, leading the way for a new generation of adaptive vibrations-based energy harvesters