Abstract: A signal connector comprises: a first part, having at least one electrical contact part, and a first body configured to be electrically insulating; a second part, having at least one electrical pin, and a second body configured to be electrically insulating and separate from the first body, and the electrical pin is configured to protrude from the second body; and an electrical connection body, extending from each electrical contact part to each electrical pin, in order to establish an electrical connection between the electrical contact part and the electrical pin, wherein the electrical connection body is configured to be deformable and comprises at least two bending parts, and at least part of the electrical connection body is located outside the first part and the second part, such that the position of the second part relative to the first part is variable.

Abstract: Systems, devices, and methods for washing robotic cleaners are disclosed. An example robotic cleaning system may include a robotic cleaner, which may include a housing and at least one wet cleaning element including at least one cleaning surface on an underside of the housing. A docking station may include a base. A support may extend laterally from the base. The support may be configured to receive at least a portion of the robotic cleaner on top of the support. The support may define a cavity. At least one cleaning shuttle may be within the cavity and may include at least one spray nozzle and at least one mechanical contacting element. The spray nozzle(s) may be configured to spray cleaning fluid onto at least a first portion of the cleaning surface(s). The mechanical contacting element(s) may be configured to contact at least a second portion of the cleaning surface(s).

Abstract: A method, system, and computer program product are provided for generating a predictive model. A processor(s) obtains a raw data set (peptide libraries) of patients designated as diagnosed/pre-diagnosed with a condition or not diagnosed with the condition. The processor(s) segments the raw data set into a pre-defined number of groups and separates out a holdout group. The processor(s) performs a principal component analysis on the remaining groups to identify, based on a frequency of features in the remaining groups, common features (principal components) in the remaining groups and weighs the common features based on frequency of occurrence. The processor(s) determines a smallest number of the principal components that yields a pre-defined level of validation accuracy. The processor(s) generates a predictive model, by utilizing the smallest number for a best fit in a logistic regression model. The predictive model provides binary outcomes.

Abstract: A method, system, and computer program product are provided for generating a predictive model. A processor(s) obtains a raw data set (peptide libraries) of patients designated as diagnosed/pre-diagnosed with a condition or not diagnosed with the condition. The processor(s) segments the raw data set into a pre-defined number of groups and separates out a holdout group. The processor(s) performs a principal component analysis on the remaining groups to identify, based on a frequency of features in the remaining groups, common features (principal components) in the remaining groups and weighs the common features based on frequency of occurrence. The processor(s) determines a smallest number of the principal components that yields a pre-defined level of validation accuracy. The processor(s) generates a predictive model, by utilizing the smallest number for a best fit in a logistic regression model. The predictive model provides binary outcomes.

Abstract: A wall covering comprising a planar substrate having a front and a back facing opposite the front and an adhesive layer that covers the back of the substrate. The adhesive layer includes a separate polymer layer, formed by a polyvinyl alcohol polymer. Wall covering for example in the form of a pre-pasted paper is readily reactivated when wet, and exhibits no blocking, while having properties of sliding, adhesion, and stripability.

Abstract: The Itch Blower is hand held, have a way to determine the distance from the skin. It blows hot air with the right temperature for eliminating the skin itching. Most importantly, it can sense the skin temperature remotely and shut off the heating automatically so to avoid burning. This will guarantee a smooth approval from the FDA and a great success in commercialization. The device eliminates skin itching completely in just seconds, no matter how bad the itching is, and keeps the itching away for up to 24 hours, and when the itching comes back, patients can use the device to quickly blow away the itching again, so to stay itching free. It can also clear up acne and eczema for some patients.

Abstract: A method, system, and computer program product are provided for generating a predictive model. A processor(s) obtains a raw data set (peptide libraries) of patients designated as diagnosed/pre-diagnosed with a condition or not diagnosed with the condition. The processor(s) segments the raw data set into a pre-defined number of groups and separates out a holdout group. The processor(s) performs a principal component analysis on the remaining groups to identify, based on a frequency of features in the remaining groups, common features (principal components) in the remaining groups and weighs the common features based on frequency of occurrence. The processor(s) determines a smallest number of the principal components that yields a pre-defined level of validation accuracy. The processor(s) generates a predictive model, by utilizing the smallest number for a best fit in a logistic regression model. The predictive model provides binary outcomes.

Abstract: A method, system, and computer program product are provided for generating a predictive model. A processor(s) obtains a raw data set (peptide libraries) of patients designated as diagnosed/pre-diagnosed with a condition or not diagnosed with the condition. The processor(s) segments the raw data set into a pre-defined number of groups and separates out a holdout group. The processor(s) performs a principal component analysis on the remaining groups to identify, based on a frequency of features in the remaining groups, common features (principal components) in the remaining groups and weighs the common features based on frequency of occurrence. The processor(s) determines a smallest number of the principal components that yields a pre-defined level of validation accuracy. The processor(s) generates a predictive model, by utilizing the smallest number for a best fit in a logistic regression model. The predictive model provides binary outcomes.

Abstract: For the purpose of preparing and isolating diamagnetic nanoparticles, we add magnetic field into the preparation processes, so that impurities that can be attracted to a magnet will go to the magnetic source. This enables diamagnetic nanoparticles get purified and contain no such impurities, so that they will be pushed away from the magnetic source. Some preparation processes use evaporation and condensation to prepare nanoparticles. In such processes, we may control the temperature so that lower evaporating metals, such as bismuth, will evaporate, but higher evaporating metals, such as iron, will stay solid and retain a strong magnetism, so that, when we apply magnetic field, we can prepare bismuth nanoparticles that do not contain lower evaporating metals for the preparation process.

Abstract: A method, system, and computer program product are provided for generating a predictive model. A processor(s) obtains a raw data set (peptide libraries) of patients designated as diagnosed/pre-diagnosed with a condition or not diagnosed with the condition. The processor(s) segments the raw data set into a pre-defined number of groups and separates out a holdout group. The processor(s) performs a principal component analysis on the remaining groups to identify, based on a frequency of features in the remaining groups, common features (principal components) in the remaining groups and weighs the common features based on frequency of occurrence. The processor(s) determines a smallest number of the principal components that yields a pre-defined level of validation accuracy. The processor(s) generates a predictive model, by utilizing the smallest number for a best fit in a logistic regression model. The predictive model provides binary outcomes.

Abstract: A method, system, and computer program product are provided for generating a predictive model. A processor(s) obtains a raw data set (peptide libraries) of patients designated as diagnosed/pre-diagnosed with a condition or not diagnosed with the condition. The processor(s) segments the raw data set into a pre-defined number of groups and separates out a holdout group. The processor(s) performs a principal component analysis on the remaining groups to identify, based on a frequency of features in the remaining groups, common features (principal components) in the remaining groups and weighs the common features based on frequency of occurrence. The processor(s) determines a smallest number of the principal components that yields a pre-defined level of validation accuracy. The processor(s) generates a predictive model, by utilizing the smallest number for a best fit in a logistic regression model. The predictive model provides binary outcomes.

Abstract: With externally applied magnetic fields, we will concentrate in vivo diamagnetic Bismuth particles or unipolar magnetic particles as a confined locus, then push the locus to move to a tumor, shape it to the tumor, then use near IR to heat the particles so to destroy the tumor by thermal ablation or hyperthermia treatment. We will then cause the locus to move to other tumors, and repeat the process, so to destroy all tumors and cure the cancer.

Abstract: With externally applied magnetic fields, we will push and concentrate in vivo diamagnetic Bismuth particles or unipolar magnetic particles as a confined locus, cause the locus to move to a tumor, shape it to the tumor, then use near IR to heat the particles so to destroy the tumor by thermal ablation or hyperthermia treatment. We will then cause the locus to move to other tumors, and repeat the process, so to destroy all tumors and cure the cancer.

Abstract: A reactor for the quantitative analysis of target nucleic acids using an evanescent wave detection technique and a method of use thereof is provided. The reactor includes a substrate with a cavity, a buffer layer arranged over the substrate; a cover plate arranged over the buffer layer, and inlet and outlet ports. The reactor is thermally and chemically stable for PCR processing and suitable for an evanescent wave detection technique.

Abstract: A programmable probe design of DNA micro array and detection methodology is provided. DNA probes, which are complemented with the target DNA, are designed and classified into groups according to optimum hybridization temperature. The probes are arrayed by the group and immobilized on the substrate surface of the DNA micro array. The control system, imaging system and temperature control system are programmed to cooperate with each other during the detection process. This design increases the detection capabilities of the parallel-analysis system.

Abstract: A method and apparatus for real-time, simultaneous, qualitative measurement of one or more single nucleotide polymorphisms in one or more target nucleic acids is provided. This method involves combining a polymerase chain reaction (PCR) technique with an evanescent wave technique.

Abstract: A method and apparatus for real-time, simultaneous, qualitative measurement of one or more single nucleotide polymorphisms in one or more target nucleic acids is provided. This method involves combining a polymerase chain reaction (PCR) technique with an evanescent wave technique.

Abstract: An apparatus includes a porous membrane for retaining antigens from a sample as the sample passes through the membrane. The apparatus also includes a first binding region within the membrane. The first binding region includes antibodies associated with a first antigen of interest. At least some of the antigens retained in the membrane are brought into contact with the first binding region by applying an electrophoresis field across the membrane. The porous membrane could also include an electrophoresis buffer. A presence of the first antigen of interest could be detected by exposing the first binding region to a chemiluminescent reagent, and a quantity of the first antigen of interest could be determined by performing a chemiluminescent assay on the binding region.