Rapid antimicrobial susceptibility testing (AST) is a method for quickly determining the most effective antibiotic therapy for patients with bacterial infections. These techniques enable the detection and quantification of antibiotic-resistant and susceptible bacteria metabolites at concentrations near or below ng/mL in complex media. Employing bacterial metabolites as a sensing platform, the system integrates machine learning data analysis processes to differentiate between antibiotic susceptibility and resistance in clinical infections within an hour. With the results, a clinician can prescribe appropriate medicine for the patient's bacterial infection.

Gas diffusion electrodes are used in electrochemical applications to produce value added chemicals such as H2O2. Carbon paper and carbon cloth are used as substrates in gas diffusion cathodes. However, carbon-based substrates are not mechanically sturdy as they can develop cracks under flexion. They are also expensive ($150 for a 310-micron thick carbon paper of 40cm X 40cm). UC Berkeley researchers have created air-cathodes made with a non-reacting metal mesh as the supporting conducting substrate. The metal may be in the form of an alloy or coating, such as one metal on another, or a metal coating on a non-metal substrate.  The metal air cathodes avoid the use of carbon paper altogether, are more cost effective, flexible yet strong and durable, and provide robust gas-diffusion cathodes for sustained production of H2O2 over long-periods of operation.  

An increase in threatening situations in school environments requires individuals to be ready to secure egress doors quickly to prevent intruders and other uninvited individuals from entering a space. Given the numerous variables that can affect where, when, how, or even if individuals can shelter-in-place during an emergency, there is a need for a simple, portable, lightweight, and cost-effective door security device that installs quickly and easily—without tools—on outward swinging doors from within the room being secured. The inventors have developed a device that can secure an outward swinging egress door from within a room, enabling occupants of a space to quickly barricade a room's entrance during a lockdown or other emergency requiring shelter-in-place protocols. In contrast to other known door security devices and systems for securing a hinged, outward swinging egress door, this improved door security device is portable, lightweight, easy-to-install without tools, and adaptable to doors with different handle, jamb, and casing combinations or measurements. This discrete, on-the-go security device for securing an outward swinging door is not dependent on any furnishings or security apparatus of a particular space. 

Certain difficult optimization problems, such as the traveling salesman problem, can be solved using so-called analog Ising machines, in which electronic components (such as certain arrangements of diodes or electronic switches) implement an analog of a well-studied physical system known as an Ising machine. The problem is recast so that its solution can be read off from the lowest-energy configuration of the analog Ising machine, a state which the system will naturally evolve towards. While promising, this methodology suffers major drawbacks. Firstly, the number of subunits, known as “spins”, in the analog Ising machines, as well as the number of connections between these subunits, can grow substantially with problem size. Secondly, existing implementations of this principle rely on chip constructions which are optimized for one or a few problems, and are not sufficiently reprogrammable to be repurposed efficiently for other applications. To address these problems, researchers at UC Berkeley have developed a device known as a Field-programmable Ising machine which can be adapted to implement an analog Ising machine using a variety of hardware designs, such as the diodes and switches mentioned above. These Ising machines can be effectively reprogrammed to efficiently solve a wide array of problems across various domains. The inventors have shown that this design can be applied to SAT (“Satisfiability”) problems, a class known to be similar to the traveling salesman problem, in that the number of spins needed and their level of connectivity do not grow too quickly with problem size.

Metamaterials are constructed from regular patterns of simpler constituents known as unit cells. These engineered metamaterials can exhibit exotic mechanical properties not found in naturally occurring materials, and accordingly they have the potential for use in a variety of applications from running shoe soles to automobile crumple zones to airplane wings. Practical design using metamaterials requires the specification of the desired mechanical properties based on understanding the precise unit cell structure and repeating pattern. Traditional design approaches, however, are often unable to take advantage of the full range of possible stress-strain relationships, as they are hampered by significant nonlinear behavior, process-dependent manufacturing errors, and the interplay between multiple competing design objectives. To solve these problems, researchers at UC Berkeley have developed a machine learning algorithm in which designers input a desired stress-strain curve that encodes the mechanical properties of a material. Within seconds, the algorithm outputs the digital design of a metamaterial that, once printed, fully encapsulates the desired properties from the inputted stress-strain curve. This algorithm produces results with a fidelity to the desired curve in excess of 90%, and can reproduce a variety of complex phenomena completely inaccessible to existing methods.

The inventors have developed an engineering approach to identify novel and nonobvious membrane-associated accessory protein (MAAP) sequence variants that confer increased Adeno-associated virus (AAV) secretion during packaging. The technique is based upon the iterative process of sequence diversification and selection of functional gene variants known as directed evolution. First, the inventors generated a library of more than 1E6 MAAP variants. The variants were subjected to five rounds of packaging into an AAV2 capsid for which MAAP expression was inactivated without altering the viral protein VP1 open reading frame (ORF) (AAV2-MAAP-null). Among each iterative packaging round, the inventors observed a progressive increase in both the overall titer and ratio of secreted vector genomes conferred by the bulk selected MAAP library population. Next-generation sequencing uncovered common mutational features that were enriched up to over 10,000-fold on the amino acid level. Individual MAAP variants were isolated and systematically tested for effect on recombinant AAV2-MAAP-null packaging in HEK293 cells. The inventors predict that this work may be applicable to increasing per-cell AAV output in industrial settings, potentially reducing global costs and increasing functional vector recovery in downstream manufacturing processes.BACKGROUNDParvoviruses are small, single-stranded DNA viruses that are ubiquitously found in many animal species. AAV is a prototypic dependoparvovirus whose replication cycle requires the function of helper genes from larger co-infected viruses such as Adenoviruses or Herpesviruses. The natural genome of AAV contains ~4.7 kb of ssDNA that encodes up to ten known proteins in a highly overlapped fashion. The rep gene encodes four protein products named based on their molecular weight: Rep72 and Rep68 facilitate genomic replication, whereas Rep52, and Rep40 play essential roles in loading nascent ssDNA genomes into assembled capsids. Downstream of rep lies the cap gene, which encodes three known protein products off of overlapping reading frames: VP1, VP2, and VP3 are structural proteins that assemble to form the capsid, the assembly activating protein (AAP) targets VP proteins to the nucleus and is involved in capsid assembly. The most recently discovered AAV-encoded gene is the membrane-associated accessory protein (MAAP). MAAP is encoded by an alternative ORF in the AAV cap gene that is found in all presently reported natural serotypes. Gene delivery by recombinant AAV (rAAV) have shown significant success in both research and clinical gene therapy applications. In the rAAV system, Rep and Cap are removed from between AAV’s 5’ and 3’ inverted terminal repeats (ITRs) and provided in trans. Instead, a transgene of interest is inserted between the ITRs and subsequently packaged into the nascent AAV capsids. However, manufacturing quantities of good manufacturing practice (GMP)-grade rAAVs necessary to achieve current and projected dosing requirements–particularly in a clinical context–presents a significant hurdle to expanding rAAV-based gene therapies. Recently, evidence has emerged supporting a functional role of MAAP in AAV egress. This led to the hypothesis that MAAP could be engineered to facilitate increased levels of secreted AAV produced from HEK293 cells. 

The inventors have developed a method of mutagenizing user-defined regions of cytoplasmic DNA using a single guide RNA (sgRNA) or combinations of sgRNAs and a highly engineered fusion polypeptide comprising: a nuclear export sequence (NES)-containing, engineered nuclear localization sequence (NLS)-lacking, enzymatically active, RNA-guided endonuclease that introduces a single-stranded break in cytoplasmic DNA, and an error-prone DNA polymerase. This novel technology encompasses and provides evidence for the use of RNA-guided nucleases with relaxed PAM requirements, which are particularly useful for AT-rich targets such as the vaccinia virus genome. The inventors show that the truncation of up to several base pairs from the PAM-distal template binding region of the sgRNAs significantly increases the functional activity and specificity of the targeted mutagenesis complex. Moreover, the invention describes specific methods for the use of this technology to edit cytoplasmically replicating viruses with large DNA genomes, using poxviruses as a model system. The novel editing platform and methods selectively and continuously accelerate diversification of user-defined sites in the vaccinia genome during infection, while retaining most library members, due to significantly lowering deleterious off-target mutations. BACKGROUND Nucleocytoplasmic large DNA viruses (NCLDVs) are a group of viruses that harbor large (150 kbp - 1.2 mbp) double-stranded DNA genomes and replicate in the cytoplasm of eukaryotic cells. An example of an NCLDV that has historically been among the most prominent tools in human health is vaccinia, a poxvirus. Hundreds of millions of humans have been intentionally inoculated with vaccinia as part of a global effort to eliminate smallpox, which was declared eradicated in 1980.Vaccinia and some other poxviruses remain highly scientifically relevant in the post-eradication world. They are useful as vaccines against deadly poxvirus outbreaks that could potentially arise from natural spillover, bioterrorism, or biowarfare, as well as due to their therapeutic promise as oncolytic agents to selectively deliver anti-cancer transgenes and recruit adaptive immunity while leaving healthy cells unharmed. Directed evolution is a powerful engineering technique for evolving new phenotypes that are beneficial for biotechnological applications but for which there may have never been a selective pressure to evolve in nature. Both natural and directed evolution depend upon generation of genetic diversity, followed by a selective pressure. While natural evolution generates genetic diversity randomly and throughout the entirety of the genome, directed evolution ideally focuses mutations within specific genomic windows connected to the phenotype that one wishes to engineer. However, there is a need in the art for compositions and methods for mutagenizing a target DNA in the cytoplasm of mammalian cells. NCLDVs, which either partially or entirely express their own replicative and translational machinery independent of the nucleus, are difficult, and in many cases impossible, to produce from plasmid DNA in cells. Thus, NCLDVs are not amenable to standard in vitro molecular diversification strategies.  

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Researchers at the University of California, Davis have developed several blockchain paradigms that provide new approaches and expand on existing protocols to improve performance in large-scale blockchain implementations.

The inventors have developed a highly scalable multiplexed approach to increase the density of graphene nanoribbon- (GNR) based transistors. The technology forms a single device/chip (scale to 16,000 to >1,000,000 parallel transistors) on a single integrated circuit for single molecule biomolecular sensing, electrical switching, magnetic switching, and logic operations. This work relates to the synthesis and the manufacture of molecular electronic devices, more particularly sensors, switches, and complimentary metal-oxide semiconductor (CMOS) chip-based integrated circuits.Bottom-up synthesized graphene nanoribbons (GNRs) have emerged as one of the most promising materials for post-silicon integrated circuit architectures and have already demonstrated the ability to overcome many of the challenges encountered by devices based on carbon nanotubes or photolithographically patterned graphene. The new field of synthetic electronics borne out of GNRs electronic devices could enable the next generation of electronic circuits and sensors.  

Researchers at the University of California, Davis have developed an amplifier technology that boosts power output in order to improve data transmission speeds for high-frequency communications.

Electromagnetic noise from surfaces is one of the limiting factors for the performance of solid state and trapped ion quantum information processing architectures. This noise introduces gate errors and reduces the coherence time of the systems. Accordingly, there is great commercial interest in reducing the electromagnetic noise generated at the surface of these systems.Surface treatment using ion bombardment has shown to reduce electromagnetic surface noise by two orders of magnitude. In this procedure ions usually from noble gasses are accelerated towards the surface with energies of 300eV to 2keV. Until recently, commercial ion guns have been repurposed for surface cleaning. While these guns can supply the ion flux and energy required to prepare the surface with the desired quality, they are bulky and limit the laser access, making them incompatible with the requirements for ion trap quantum computing.To address this limitation, UC Berkeley researchers have developed an ion gun that enables in-situ surface treatment without sacrificing high optical access, enabling in situ use with a quantum information processor.

Portable UAVs such as quad-copters have made huge inroads in the last several years in various fields of aerial photography and surveillance. Drones can efficiently and cheaply hover over/follow a target of interest and capture unique perspectives of wildlife, real-estate, sporting events and operational environments such as law enforcement or military. More challenging however is the application of UAVs for large area search and surveillance. In these scenarios, a search pattern must be established which can cover many square miles and is far too expansive for a UAVs typical battery to sustain. To make UAVs more broadly effective in large area search and target identification, new path planning algorithms are needed to efficiently eliminate areas of low probability while focusing on search areas most likely to contain the subject of interest. Likewise, improved image classifiers are needed to aid in separating targets of interest from background terrain, thus expediting the search within given battery limitations

A microfluidic platform for real time sensing of volatile airborne agents.

This technology is a new class of materials capable of thermal regulation and active camouflage. These cephalopod-inspired materials, configurable to different geometries, can be used in many sectors, ranging from consumer to industrial to military applications.

Researchers led by Dr. Potkonjak from the UCLA Department of Computer Science have developed a technique to detect hardware Trojans in integrated circuits.

Professor Jonathan Hopkins and colleagues have developed amechanical programmable metamaterial consisting of an array of actively, independently controlled micro-scale unit cells. This technology allows for the application of materials which have instantly changeable, programmable properties that can exceed those of conventional, existing materials.

UCLA researchers in the Department of Computer Science have developed a novel way in which to secretly search for and collect relevant information from a streaming database. The invention has application to intelligence gathering and data mining.

Researchers at UCI have developed a novel method for encrypting optical communications, which is simpler, less expensive, and less computationally-demanding than standard solutions.

Nanocrystalline iron nitride is an important soft magnetic material; however, conventional methods of production don’t exist. Synthesis of dense nanocrystalline iron nitrides is not possible by simply annealing elemental iron in NH3 at temperatures in excess of 600° C since g’-Fe4N and other iron nitrides are unstable above 600°C and will decompose. Sandia researchers have discovered that by using a two-step reactive milling process and high pressure spark plasma sintering (SPS) they can quickly and efficiently fabricate bulk g’-Fe4N parts.

In our electronically connected society, human identification systems are critical to secure authentication, and also enabling for tailored services to individuals. Conventional human identification systems, such as biometric-based or vision-based approaches, require either the deployment of dedicated infrastructure, or the active cooperation of users to carry devices. Consequently, pervasive implementation of conventional human identification systems is expensive, inconvenient, or intrusive to privacy. Recently, WiFi infrastructure, and associated WiFi-enabled mobile and IoT devices have become ubiquitous, and correspondingly, have enabled many context-aware and location-based services. To address the challenges of human identification systems and take advantage of the popularity of WiFi, researchers at UC Berkeley developed a human identification system based on analyzing signals from existing WiFi-enabled devices. This novel device-free approach uses WiFi signal analysis to reveal the unique, fine-grained gait patterns of individuals as the "fingerprint" for human identification.

This technology combines air layer frictional drag reduction (ALDR) with super hydrophobic surfaces (SHS) to achieve frictional drag reduction of ALDR with significantly reduced gas flux. Thus, enabling increased net energy savings. The stable air layer is achieved with lesser gas flux when utilizing a SHS.Periodic air layers may replenish SHS, enabling drag reduction with reduced energy cost. Combinations of SHS and regular or other non-SHS surface may be used to control spreading of gas, thus facilitating formation of ALDR using discrete gas injection points better than previously achievable. Such surface variations could also be used to preferentially guide gas towards or away from propulsion, depending on desired outcome. By controlling ALDR regionally or globally on a surface, with or without SHS, this technology modifies flow around a hull. This mediates forces on partially or fully submerged objects, enabling control of flow patterns, resistance, steering, and/or dynamics.

Researchers at the University of California, Davis have developed a new flight mechanism that offers vertical take-off and landing (VTOL) capability and cruising speeds comparable with fixed wing unmanned aerial vehicles (UAV).