Reduced Gonadotrophin Receptor Expression Is Associated with a More Aggressive Ovarian Cancer Phenotype

Follicle-stimulating hormone (FSH) and luteinising hormone (LH) play important roles in regulating cell growth and proliferation in the ovary. However, few studies have explored the expression of FSH and LH receptors (FSHR and LHCGR) in ovarian cancer, and their functional roles in cancer progression remain inconclusive. This study investigated the potential impact of both mRNA (FSHR, LHCGR) and protein (FSHR, LHCGR) expression on ovarian cancer progression using publicly available online databases, qRT-PCR (high grade serous ovarian cancers, HGSOC, n = 29 and benign ovarian tumors, n = 17) and immunohistochemistry (HGSOC, n = 144). In addition, we investigated the effect of FSHR and LHCGR siRNA knockdown on the pro-metastatic behavior of serous ovarian cancer cells in vitro. High FSHR or high LHCGR expression in patients with all subtypes of high-grade ovarian cancer was significantly associated with longer progression-free survival (PFS) and overall survival (OS). High FSHR protein expression was associated with increased PFS (p = 0.050) and OS (p = 0.025). HGSOC patients with both high FSHR and high LHCGR protein levels had the best survival outcome, whilst both low FSHR and low LHCGR expression was associated with poorest survival (p = 0.019). Knockdown of FSHR significantly increased the invasion of serous ovarian cancer cells (OVCAR3 and COV362) in vitro. LHCGR knockdown also promoted invasion of COV362 cells. This study highlights that lower FSHR and LHCGR expression is associated with a more aggressive epithelial ovarian cancer phenotype and promotes pro-metastatic behaviour.     

Effect of multi-ions doping on the properties of carbonated hydroxyapatite bioceramic

The effect of multi-ions (Mg²⁺, SiO₄^4-, Zn²⁺, Cu²⁺) doping on the properties of carbonated hydroxyapatite (CHA) prepared by a wet chemical method has been investigated. Different combinations of ions were doped into the CHA and the as-synthesized compacts were sintered at 900?°C prior to body characterization. It was found that regardless of ions doping, the lattice structure of the CHA was not disrupted. In addition, secondary phases were not detected for all the multi-ions doped samples. The XRD and FTIR results further confirmed the presences of a B-Type CHA in the sintered samples. The XRD analysis revealed that the lattice parameters (c/a ratio) increased with dopant addition and resulted in a smaller crystallite size. The FESEM examination also showed the presences of smaller grain size for the multi-ions doped CHA samples thus indicating that the doping was beneficial in suppressing grain coarsening in carbonated hydroxyapatite.     

An effective back‐off selection technique for reliable beacon reception in VANETs

In safety‐critical scenarios, reliable reception of beacons transmitted by a subject vehicle is critical to avoid vehicle collision. According to the employed contention window sizes in IEEE 802.11p, beacons are transmitted with a small contention window size. As a result, multiple vehicles contend for the shared channel access by selecting the same back‐off slot. This is a perfect recipe for synchronous collisions wherein reliable beacon delivery cannot be guaranteed for any vehicle. We consider the problem of selecting the back‐off slots from the current contention window to provide reliable delivery of beacons transmitted by a subject vehicle to its neighbors. Given a safety scenario, we propose a Pseudo‐Random Number Generator (PRNG)‐inspired back‐off selection (PBS) technique. The proposed technique works on the hypothesis that synchronous collisions of beacons transmitted by a subject vehicle can be reduced if all its neighbors select different back‐off slots (ie, not the back‐off slot selected by the subject vehicle). The discrete‐event simulations demonstrate that PBS can increase the overall message reception from a subject vehicle, in comparison with the uniform random probability back‐off selection in IEEE 802.11p.     

Effect of Various Surfactants on the Viscosity,Thermal and Electrical Conductivity of Graphene Nanoplatelets Nanofluid

International Journal of Thermophysics - The paper describes the metrological characterization of the highly stable Pt-40%Rh/Pt-6%Rh thermocouples to determine their reference function in the...     

A Novel Artificial Intelligence Based Timing Synchronization Scheme for Smart Grid Applications

The smart grid control applications necessitate real-time communication systems with time efficiency for real-time monitoring, measurement, and control. Time-efficient communication systems should have the ability to function in severe propagation conditions in smart grid applications. The data/packet communications need to be maintained by synchronized timing and reliability through equally considering the signal deterioration occurrences, which are propagation delay, phase errors and channel conditions. Phase synchronization plays a vital part in the digital smart grid to get precise and real-time control measurement information. IEEE C37.118 and IEC 61850 had implemented for the synchronization communication to measure as well as control the smart grid applications. Both IEEE C37.118 and IEC 61850 experienced a huge propagation and packet delays due to synchronization precision issues. Because of these delays and errors, measurement and monitoring of the smart grid application in real-time is not accurate. Therefore, it has been investigated that the time synchronization in real-time is a critical challenge in smart grid applications, and for this issue, other errors raised consequently. The existing communication systems are designed with the phasor measurement unit (PMU) along with communication protocol IEEE C37.118 and uses the GPS timestamps as the reference clock stamps. The absence of GPS increases the clock offsets, which surely can hamper the synchronization process and the full control measurement system that can be imprecise. Therefore, to reduce this clock offsets, a new algorithm is needed which may consider any alternative reference timestamps rather than GPS. The revolutionary Artificial Intelligence (AI) enables the industrial revolution to provide a significant performance to engineering solutions. Therefore, this article proposed the AI-based Synchronization scheme to mitigate smart grid timing issues. The backpropagation neural network is applied as the AI method that employs the timing estimations and error corrections for the precise performances. The novel AIFS scheme is considered the radio communication functionalities in order to connect the external timing server. The performance of the proposed AIFS scheme is evaluated using a MATLAB-based simulation approach. Simulation results show that the proposed scheme performs better than the existing system.

     

Speeding up dynamic time warping distance for sparse time series data

Dynamic time warping (DTW) distance has been effectively used in mining time series data in a multitude of domains. However, in its original formulation DTW is extremely inefficient in comparing long sparse time series, containing mostly zeros and some unevenly spaced nonzero observations. Original DTW distance does not take advantage of this sparsity, leading to redundant calculations and a prohibitively large computational cost for long time series. We derive a new time warping similarity measure (AWarp) for sparse time series that works on the run-length encoded representation of sparse time series. The complexity of AWarp is quadratic on the number of observations as opposed to the range of time of the time series. Therefore, AWarp can be several orders of magnitude faster than DTW on sparse time series. AWarp is exact for binary-valued time series and a close approximation of the original DTW distance for any-valued series. We discuss useful variants of AWarp: bounded (both upper and lower), constrained, and multidimensional. We show applications of AWarp to three data mining tasks including clustering, classification, and outlier detection, which are otherwise not feasible using classic DTW, while producing equivalent results. Potential areas of application include bot detection, human activity classification, search trend analysis, seismic analysis, and unusual review pattern mining.     

A new spatial spherical pattern model into interactive cartography pattern: multi-dimensional data via geostrategic cluster

A growing amount of research conducted in digital, cooperative with advances in Artificial Intelligence, Computer Vision including Machine learning, has managed to the advance of progressive techniques that aim to detect and process affective information contained in multi-modal evidences. This research intends to bring together for theoreticians and practitioners from academic fields, professionals and industries and extends to be visualizing cries such epidemic, votes, social Phenomena in spherical representation interactive model working in the broad range of topics relevant to multi - modal data processing and forensics tools developing. Furthermore, progress has been made in this research besides that in this research conducted progression of mapping claims in present epoch necessitate the capacities of virtual guide of any understandable Geo-Visualization of spatial features that talented to convert the quantities of spatial pattern into cartography. The enlargement of a novel approaches fit for visualization of spatial pattern constituencies Starting exclusive Input Set of object O, set associated with feature F for regenerating Output the set C , interested region I special target C Even so, as indicated by the construction of the prototype as listed earlier in this thread, does it have the incentive for improvements: Representation could be used by Google Earth can Using Project enhancement representation whereby provides a 3D or 4D interaction with life measures with a view to cartography. In addition, the initiative suggests that a tool not accessible for disseminating information to the public can be addressed by the use of online mapping, which fuses with trends visualization for political circles and electors. But as mentioned above the framework is developed and it's also possible in the current example, for improvements: The project's representation 3D or 4D interacting Earth can use measures of life Earth From the map viewpoint. That's what that says. That means that. Which just means. Developers have concerns that. So it. Designers concern about that. This study supports the new, multi - demission and deployed countries in conjunction with another data is processed. Comprehensive, well-interpreted source data for the Data like Malaysia Jabatan Pendaftaran (JPN).

     

The development of spectral indices for early detection of Ganoderma disease in oil palm seedlings

Field spectroscopy is a rapid and non-destructive analytical technique that may be used for assessing plant stress and disease. The objective of this study was to develop spectral indices for detection of Ganoderma disease in oil palm seedlings. The reflectance spectra of oil palm seedlings from three levels of Ganoderma disease severity were acquired using a spectroradiometer. Denoizing and data transformation using first derivative analysis was conducted on the original reflectance spectra. Then, comparative statistical analysis was used to select significant wavelength from transformed data. Wavelength pairs of spectral indices were selected using optimum index factor. The spectral indices were produced using the wavelength ratios and a modified simple ratio method. The relationship analysis between spectral indices and total leaf chlorophyll (TLC) was conducted using regression technique. The results suggested that six spectral indices are suitable for the early detection of Ganoderma disease in oil palm seedlings. Final results after regression with TLC showed that Ratio 3 is the best spectral index for the early detection of Ganoderma infection in oil palm seedlings. For future works, this can be used for the development of robust spectral indices for Ganoderma disease detection in young and mature oil palm using airborne hyperspectral imaging.     

Oligomeric Composition of Polyols From Fatty Acid Methyl Ester: The Effect of Ring‐Opening Reactants of Epoxide Groups

Commercial availability of fatty acid methyl ester (FAME) from palm oil targeted for biodiesel offers a good feedstock for the production of structurally well‐defined polyols for polyurethane applications. The effect of molecular weight (MW), odd and even carbon numbers, and the linear and branched structure reactants used in the ring‐opening reaction of epoxidized fatty acid methyl ester (E‐FAME) on the properties of polyols was investigated. Conversions of E‐FAME to PolyFAME polyols were confirmed by Fourier transform infrared analysis, oxirane oxygen content, and hydroxyl number. Gel permeation chromatography (GPC) calibrated against polyether polyols as a standard and vapor pressure osmometry were used for MW determination. GPC chromatograms of PolyFAME polyols clearly demonstrated the formation of oligomers during ring‐opening reactions. MW, and odd and even carbon numbers in a structure of linear diols and branched diol used in the syntheses of PolyFAME polyols did not have an effect on crystallinity, glass transition, or melt temperatures measured using Differential scanning calorimetry (DSC). PolyFAME polyols ring‐opened with water, methanol, and 1,2‐propanediol contained secondary hydroxyl groups, whereas PolyFAME polyols ring‐opened with linear diols contained a mixture of primary and secondary hydroxyl groups. It was found that the concentration of primary hydroxyl groups increased significantly by increasing the number of carbons from C2 to C3 in the linear diols. The viscosity of PolyFAME polyols also increased with the MW of linear diols used in the E‐FAME ring‐opening reaction. These findings would be beneficial for formulators in choosing the most cost effective polyols for polyurethane formulations.     

Effects of Ni doping on photocatalytic activity of TiO<Subscript>2</Subscript> thin films prepared by liquid phase deposition technique

The TiO₂ thin films doped by Ni uniformly and non-uniformly were prepared on glass substrate from an aqueous solution of ammonium hexa-fluoro titanate and NiF₂ by liquid phase deposition technique. The addition of boric acid as an F ⁻ scavenger will shift the equilibrium to one side and thereby deposition of the film is progressed. The rate of the reaction and the nature of deposition depend on growing time and temperature. The resultant films were characterized by XRD, EDAX, UV and SEM. The result shows that the deposited films have amorphous background, which becomes crystalline at 500°C. The EDAX data confirms the existence of Ni atoms in TiO₂ matrix. XRD analysis reveals the peaks corresponding to Ni but no peak of crystalline NiO was found. The transmittance spectra of Ni uniformly and non-uniformly doped TiO₂ thin films show ‘blue shift and red shift’, respectively. Ni-doped TiO₂ thin films can be used as photocatalyst for the photodegradation of methyl orange dye. It was found that, organic dye undergoes degradation efficiently in presence of non-uniformly Ni-doped TiO₂ thin films when compared to uniformly doped films and pure TiO₂ films under visible light. The photocatalytic activity increases with increase in the concentration of Ni in case of nonuniformly doped thin films but decreases with the concentration when uniformly doped thin films were used.