Miracle-dz/UniFAR-FTUs huggingface dataset:
Ultracold Molecules in Optical Lattices: Efficient Production and Application to Molecular Clocks

Abstract : We have established the strontium molecular clock as the leading ultracold-molecule precision measurement platform. We can fully control the molecules internal and external quantum states, as in state-of-the-art atomic lattice clocks. Using the quantized molecular spectra in an optical lattice, we devised a new lattice thermometry method that is advantageous for many lattice experiments, including clocks and manybody physics studies. The full quantum control allowed us to observe deeply subradiant molecular states, and coherently control them. We measured lifetimes enhanced by up to 300 times. Ultranarrow transitions to these states permitted a rigorous study of asymptotic physics at the atom-molecule threshold. We proved that subradiant states can decay to the ground state via higher-order electromagnetic transitions, with a rate that grows as the square of the bond length, and are quenched by predissociation at a rate proportional to the vibrational level spacing. We introduced a precise technique for measuring molecular binding energies via photofragmentation; controlled forbidden optical transition strengths with weak magnetic fields by five orders of magnitude; and explained anomalously large magnetic susceptibilities of the asymptotic molecules. The unprecedented precision, coupled with advanced ab initio theory, paves the way to exciting new directions for the molecular clock.
Passive Multifrequency Forward-Scatter Radar Measurements of Airborne Targets Using Broadcasting Signals

This paper demonstrates the feasibility and effectiveness of forward-scatter radar (FSR) target detection based on the signals of opportunity made available by standard radio and TV broadcast transmission stations. This passive FSR (P-FSR) operation is obtained by means of a simple and robust correlation process based on self-mixing. This is shown to be very effective in extracting the characteristic FSR modulation produced by airborne targets, from the signals received from frequency modulated, digital audio broadcasting, and digital video broadcasting transmitters of opportunity. Target detectability is discussed as a function of the carrier frequency, the target size, and its height at the baseline crossing. Experimental results are shown using a wide variety of sources of opportunity, target types, baselines, and receiver configurations. The target signatures obtained from the different illuminators are compared and ways of extracting the kinematic parameters of the aircraft are discussed. This validates the claimed effectiveness and robustness of the P-FSR with the presented processing scheme.
Satisfying First-Order Constraints About Time Intervals

James Allen denned a calculus of time intervals in [All83], as a representation of temporal knowledge that could be used in AI. We shall call this the Interval Calculus. In his paper, Allen investigated specification and constraint satisfaction in the Interval Calculus. Other constraint-satisfaction algorithms for intervals have considered subclasses of Boolean formulas only. The methods herein extend consistency-checking and constraint-satisfaction procedures to finitely many arbitrary quantified formulas in the Interval Calculus. We use a first-order theory from [LadMad87.1, LadMad88.1], that precisely corresponds to Allen's calculus. We show that every first-order constraint expressible in this theory is equivalent to a Boolean constraint of a particular restricted form. We use this result to obtain a procedure for detecting consistency of arbitrary quantified formulas, and finding intervals that satisfy arbitrary consistent formulas of the Interval Calculus.
ADBP-1 Regulates an ADAR RNA-Editing Enzyme to Antagonize RNA-Interference-Mediated Gene Silencing in Caenorhabditis elegans

Small interfering RNAs (siRNAs) and microRNAs (miRNAs) mediate gene silencing through evolutionarily conserved pathways. In Caenorhabditis elegans, the siRNA/miRNA pathways are also known to affect transgene expression. To identify genes that regulate the efficiencies of the siRNA/miRNA pathways, we used the expression level of a transgene as an indicator of gene silencing and isolated a transgene-silencing mutant, adbp-1 (ADR-2 binding protein). The adbp-1 mutation caused transgene silencing in hypodermal and intestinal cells in a cell-autonomous manner, depending on the RNA interference (RNAi) machinery. The adbp-1 gene encodes a protein with no conserved domains that is localized in the nucleus. Yeast two-hybrid screening and co-immunoprecipitation analysis demonstrated that ADBP-1 physically interacts with ADR-2, an RNA-editing enzyme from the ADAR (adenosine deaminase acting on dsRNA) family. In the adbp-1 mutant, as previously shown in adr-2 mutants, A-to-I RNA editing was not detected, suggesting that ADBP-1 is required for the RNA-editing activity of ADR-2. We found that ADBP-1 facilitates the nuclear localization of ADR-2. ADBP-1 may regulate ADR-2 activity and the consequent RNA editing and thereby antagonize RNAi-mediated transgene silencing in C. elegans.
Surface Roughness and Morphology Customization of Additive Manufactured Open Porous Ti6Al4V Structures

Additive manufacturing (AM) is a production method that enables the building of porous structures with a controlled geometry. However, there is a limited control over the final surface of the product. Hence, complementary surface engineering strategies are needed. In this work, design of experiments (DoE) was used to customize post AM surface treatment for 3D selective laser melted Ti6Al4V open porous structures for bone tissue engineering. A two-level three-factor full factorial design was employed to assess the individual and interactive effects of the surface treatment duration and the concentration of the chemical etching solution on the final surface roughness and beam thickness of the treated porous structures. It was observed that the concentration of the surface treatment solution was the most important factor influencing roughness reduction. The designed beam thickness decreased the effectiveness of the surface treatment. In this case study, the optimized processing conditions for AM production and the post-AM surface treatment were defined based on the DoE output and were validated experimentally. This allowed the production of customized 3D porous structures with controlled surface roughness and overall morphological properties, which can assist in more controlled evaluation of the effect of surface roughness on various functional properties.
Spatiotemporal Patterns of Cortical Activity with Bilateral Cochlear Implants in Congenital Deafness

Congenital deafness affects developmental processes in the auditory cortex. In this study, local field potentials (LFPs) were mapped at the cortical surface with microelectrodes in response to cochlear implant stimulation. LFPs were compared between hearing controls and congenitally deaf cats (CDCs). Pulsatile electrical stimulation initially evoked cortical activity in the rostral parts of the primary auditory field (A1). This progressed both in the approximate dorsoventral direction (along the isofrequency stripe) and in the rostrocaudal direction. The dorsal branch of the wavefront split into a caudal branch (propagating in A1) and another smaller one propagating rostrally into the AAF (anterior auditory field). After the front reached the caudal border of A1, a “reflection wave” appeared, propagating back rostrally. In total, the waves took ∼13–15 ms to propagate along A1 and return back. In CDCs, the propagation pattern was significantly disturbed, with a more synchronous activation of distant cortical regions. The maps obtained from contralateral and ipsilateral stimulation overlapped in both groups of animals. Although controls showed differences in the latency–amplitude patterns, cortical waves evoked by contralateral and ipsilateral stimulation were more similar in CDCs. Additionally, in controls, LFPs with contralateral and ipsilateral stimulation were more similar in caudal A1 than in rostral A1. This dichotomy was lost in deaf animals. In conclusion, propagating cortical waves are specific for the contralateral ear, they are affected by auditory deprivation, and the specificity of the cortex for stimulation of the contralateral ear is reduced by deprivation.
Knowledge Discovery from Legal Documents Dataset using Text Mining Techniques

few decades have witnessed exponential increase in the use of IT which has resulted into large amount of data being generated, stored and searched. Data may be highly structured stored as records of a DBMS, or may be totally unstructured like blog posts or plain text documents. With the abundance of information being available as text documents, the issue of retrieval of knowledge from such unstructured dataset is posing new challenges to the research community. Legal document analysis is one domain which generates and uses text information in semi structured as well as unstructured form. The process of legal reasoning and decision making is heavily dependent on information stored in text documents. Text Mining (TM) is defined as the process of extracting useful information from text data. Legal text documents are stored using natural languages. For efficient analysis of such documents, text mining, a specialized branch of machine learning can be suitably used. Text mining - which "mines text", is heavily associated with natural language processing and Information Retrieval. TM techniques can be used for extracting relevant knowledge from stored legal documents. The extracted knowledge is used to simplify the preparation of case base, facilitate in decision making and legal reasoning or for automatic identification of legal arguments. Research in the fields of information extraction, natural language processing, artificial intelligence and expert system has augmented text mining process for enhancing the knowledge discovery process in this domain. This paper proposes a study which is aimed at grouping of legal documents based on the contents without taking any external input using unsupervised text mining techniques.
Crowdfunding: Tapping the Right Crowd

The basic idea of crowdfunding is to raise external finance from a large audience (the “crowd”), where each individual provides a very small amount, instead of soliciting a small group of sophisticated investors. The paper develops a model that associates crowdfunding with pre-ordering and price discrimination, and studies the conditions under which crowdfunding is preferred to traditional forms of external funding. Compared to traditional funding, crowdfunding has the advantage of offering an enhanced experience to some consumers and, thereby, of allowing the entrepreneur to practice menu pricing and extract a larger share of the consumer surplus; the disadvantage is that the entrepreneur is constrained in his/her choice of prices by the amount of capital that he/she needs to raise: the larger this amount, the more prices have to be twisted so as to attract a large number of “crowdfunders” who pre-order, and the less profitable the menu pricing scheme.
Call graphs for languages with parametric polymorphism

The performance of contemporary object oriented languages depends on optimizations such as devirtualization, inlining, and specialization, and these in turn depend on precise call graph analysis. Existing call graph analyses do not take advantage of the information provided by the rich type systems of contemporary languages, in particular generic type arguments. Many existing approaches analyze Java bytecode, in which generic types have been erased. This paper shows that this discarded information is actually very useful as the context in a context-sensitive analysis, where it significantly improves precision and keeps the running time small. Specifically, we propose and evaluate call graph construction algorithms in which the contexts of a method are (i) the type arguments passed to its type parameters, and (ii) the static types of the arguments passed to its term parameters. The use of static types from the caller as context is effective because it allows more precise dispatch of call sites inside the callee. Our evaluation indicates that the average number of contexts required per method is small. We implement the analysis in the Dotty compiler for Scala, and evaluate it on programs that use the type-parametric Scala collections library and on the Dotty compiler itself. The context-sensitive analysis runs 1.4x faster than a context-insensitive one and discovers 20% more monomorphic call sites at the same time. When applied to method specialization, the imprecision in a context-insensitive call graph would require the average method to be cloned 22 times, whereas the context-sensitive call graph indicates a much more practical 1.00 to 1.50 clones per method. We applied the proposed analysis to automatically specialize generic methods. The resulting automatic transformation achieves the same performance as state-of-the-art techniques requiring manual annotations, while reducing the size of the generated bytecode by up to 5x.
Experimental and Numerical Investigation of Thin Liquid Layers at Curved Solid Edges

The knowledge of the behavior of thin liquid layers on solid surfaces is of fundamental interest as far as basic research or applications like technical coating or lubrication processes are concerned. The subject is currently getting more important, particularly due to the increasing requirements of thin liquid layer functionalities. We therefore studied the development of the liquid layer thickness distribution field as well as the liquid layer disturbance propagation on a plane solid surface in the vicinity of a curved solid surface experimentally and numerically using LIF (Laser-induced Fluorescence) and CFD (Computational Fluid Dynamics), respectively. The investigation focusses on the influence of the initial layer thickness and solid surface curvature as well as liquid properties like viscosity and surface tension on the film behavior, especially close to solid edges. Experimental and numerical results are shown pointing out relevant quantities for disturbance propagation and validation.
Using AR Technology for Automotive Visibility and Accessibility Assessment

Automotive interior ergonomics analysis is an important step for its development validation in the process, which directly affects the product development cycle time and cost. In order to provide a quick and human-in-loop visibility evaluation method for style designer when designing vehicle interior, a new method is proposed based on augmented reality. In this method, firstly virtual car interior model is superimposed to physical mockup accurately, then driving virtual visual cones through tracking eyes' position by tracking tool in real time to carry on visibility assessment. In addition, right hand's motion data is captured by data glove and tracking tool, which is used to drive virtual hand for interaction with virtual interior model, then carrying on accessibility assessment. Based on above-mentioned method the automotive interior ergonomics assessment system is designed and realized, which is verified by two cases of evaluating a certain car model's A-pillar and operating the hand controls locating on the middle dashboard in the different position. The result shows that this method is simple and useful. Therefore, it offers a new way for visibility and accessibility assessment in the conceptual design of automotive development.
Lack of correlative enhancement of passive transfer of delayed-type hypersensitivity and antilisterial resistance when using concanavalin A-stimulated primed spleen cells

The adoptive transfer of resistance to Listeria monocytogenes can be significantly enhanced by in vitro incubation of primed murine spleen cells with concanavalin A (ConA) before transfer into syngeneic recipients. The level of transferred resistance, as measured by clearance of infectious organisms, can approach that observed in actively immunized mice. When delayed-type hypersensitivity (DTH) responses of passive transfer recipients were compared, there was no difference in the level of hypersensitivity exhibited by mice receiving either nonstimulated or ConA-stimulated, Listeria-immune spleen cells. In addition, the level of these adoptively transferred responses never approached the level of DTH observed in actively immunized mice. This inability of ConA-stimulated cells to enhance passive DTH in recipient mice was not dependent on the antigenic preparation of Listeria used to elicit the DTH response. Transfer of cultured, ConA-stimulated, Listeria-immune spleen cells did not lead either to specific or to nonspecific suppression of DTH responsiveness in actively immunized mice. These results indicate the possible existence of antigen-specific T-cells subpopulations which, after stimulation with ConA, exhibit differing efficiencies when responding in assays of cell-mediated immunity.
Inter-stimulus interval study for the tactile point-pressure brain-computer interface

The paper presents a study of an inter-stimulus interval (ISI) influence on a tactile point-pressure stimulus-based brain-computer interface's (tpBCI) classification accuracy. A novel tactile pressure generating tpBCI stimulator is also discussed, which is based on a three-by-three pins' matrix prototype. The six pin-linear patterns are presented to the user's palm during the online tpBCI experiments in an oddball style paradigm allowing for “the aha-responses” elucidation, within the event related potential (ERP). A subsequent classification accuracies' comparison is discussed based on two ISI settings in an online tpBCI application. A research hypothesis of classification accuracies' non-significant differences with various ISIs is confirmed based on the two settings of 120 ms and 300 ms, as well as with various numbers of ERP response averaging scenarios.
Microplate-based, label-free detection of biomolecular interactions: applications in proteomics

This review describes a new type of label-free optical biosensor that is inexpensively manufactured from continuous sheets of plastic film and incorporated into standard format microplates to enable highly sensitive, high-throughput detection of small molecules, proteins and cells. The biosensor and associated detection instrumentation are applied to review two fundamental limiting issues for assays in proteomics research and drug discovery: requirement for quantitative measurement of protein concentration and specific activity, and measurements made with complex systems in highly parallel measurements. SRU BIosystems, Inc.’s BIND™ label-free detection will address these issues using data examples for hybridoma screening, epitope binning and mapping, small-molecule screening, and cell-based functional assays. The review describes several additional applications that are under development for the system, and the key issues that will drive adoption of the technology over the next 5 years.
Graph Convolutional Network-based Functional-structural Sub-region Framework for Head and Neck Cancer Prognosis with PET/CT Imaging

In order to improve the behavior of the prognostic model for patients with head and neck cancer (HNC), we constructed a graph convolutional network (GCN), characterizing the interaction of functional and structural information among different sub-regions of tumors in both PET and CT images. Sub-regions were obtained by using the Watershed-based method and were regarded as vertexes in the graph. The element of 1 in the adjacency matrix indicates corresponding two vertices are spatially contiguous, while the element of 0 indicates they are separated. The selected radiomics features were used to characterize each vertex. 642 HNC patients from 8 different centers were used. The best C-index of 0.767 was achieved by the combination of GCN and clinical parameters compared to the radiomics model (0.747) or GCN model (0.702). the proposed approach has great potential in aiding treatment decision-making.
Identification of Two Genes from Streptomyces argillaceus Encoding Glycosyltransferases Involved in Transfer of a Disaccharide during Biosynthesis of the Antitumor Drug Mithramycin

ABSTRACT Mithramycin is an antitumor polyketide drug produced byStreptomyces argillaceus that contains two deoxysugar chains, a disaccharide consisting of two d-olivoses and a trisaccharide consisting of a d-olivose, ad-oliose, and a d-mycarose. From a cosmid clone (cosAR3) which confers resistance to mithramycin in streptomycetes, a 3-kb PstI-XhoI fragment was sequenced, and two divergent genes (mtmGI andmtmGII) were identified. Comparison of the deduced products of both genes with proteins in databases showed similarities with glycosyltransferases and glucuronosyltransferases from different sources, including several glycosyltransferases involved in sugar transfer during antibiotic biosynthesis. Both genes were independently inactivated by gene replacement, and the mutants generated (M3G1 and M3G2) did not produce mithramycin. High-performance liquid chromatography analysis of ethyl acetate extracts of culture supernatants of both mutants showed the presence of several peaks with the characteristic spectra of mithramycin biosynthetic intermediates. Four compounds were isolated from both mutants by preparative high-performance liquid chromatography, and their structures were elucidated by physicochemical methods. The structures of these compounds were identical in both mutants, and the compounds are suggested to be glycosylated intermediates of mithramycin biosynthesis with different numbers of sugar moieties attached to C-12a-O of a tetracyclic mithramycin precursor and to C-2-O of mithramycinone: three tetracyclic intermediates containing one sugar (premithramycin A1), two sugars (premithramycin A2), or three sugars (premithramycin A3) and one tricyclic intermediate containing a trisaccharide chain (premithramycin A4). It is proposed that the glycosyltransferases encoded by mtmGI andmtmGII are responsible for forming and transferring the disaccharide during mithramycin biosynthesis. From the structures of the new metabolites, a new biosynthetic sequence regarding late steps of mithramycin biosynthesis can be suggested, a sequence which includes glycosyl transfer steps prior to the final shaping of the aglycone moiety of mithramycin.
Face Recognition based Only on Eyes' Information and Local Binary Pattern

In this paper the implementation of the Local Binary Pattern algorithm for face recognition is presented using the partial information of the face, the main contribution of this work is that segmenting the parts of face (forehead, eyes, mouth) can make the recognition a person using only their eyes and getting a percentage of up to 69%, which con- sidering the limited information provided a good success rate is obtained. In the test phase AR facedatabase it was used and using the method of Viola Jones face is located and segmented to obtain templates for each person and each part of his face and Euclidean distance was used for classication task. Because in a real application do not always have all the face of the person to identify the proposed system shows that you can get good results with partial information about it, in addition the results show that in the ranking 6 always provided the right person, which is also useful in real applications.