Miracle-dz/UniFAR-FTUs huggingface dataset:
Monolithic waveguide laser mode-locked by embedded Ag nanoparticles operating at 1 μm

Abstract Monolithic waveguide laser devices are required to achieve on-chip lasing. In this work, a new design of a monolithic device with embedded Ag nanoparticles (NPs) plus the Nd:YAG ridge waveguide has been proposed and implemented. By using Ag+ ion implantation, the embedded Ag NPs are synthesized on the near-surface region of the Nd:YAG crystal, resulting in the significant enhancement of the optical nonlinearity of Nd:YAG and offering saturable absorption properties of the crystal at a wide wavelength band. The subsequent processing of the O5+ ion implantation and diamond saw dicing of crystal finally leads to the fabrication of monolithic waveguide with embedded Ag NPs. Under an optical pump, the Q-switched mode-locked waveguide lasers operating at 1 μm is realized with the pulse duration of 29.5 ps and fundamental repetition rate of 10.53 GHz, owing to the modulation of Ag NPs through evanescent field interaction with waveguide modes. This work introduces a new approach in the application of monolithic ultrafast laser devices by using embedded metallic NPs.
1 Supporting human autonomy in AI systems

Since time immemorial humans have sought “autonomy”, the feeling that one is acting in accordance with their goals and values. Today, the meaning of, and the path towards autonomy are being reassessed in the context of the growing impact of artificial intelligence (AI). This impact is sometimes seen as a dialectical relationship where humans are in constant conflict with machines, or as a synergistic one, in which the two need to collaborate efficiently. Both perspectives fail to consider the way a technology is experienced by its users. We posit that, if AI is to support human wellbeing, developers need to consider the impact of AI on users’ experience of autonomy. We describe a model for the design of computer systems that takes autonomy into account as a basic psychological need, and we provide recommendations for designers and policy makers.
Meta Fisher Vector for event recognition in generative encoded visual streams

In this thesis we focus on event recognition in visual image streams. High level dynamic semantics such as events can often not be inferred from a single still image, but can be discovered within visual streams such as collections of images and video clips. Therefore we aim for recognition from a visual streams, rather than a single image. More specifically, we aim to construct a compact representation which encodes the diversity of the visual stream from just a few observations. For this purpose, we introduce the Meta Fisher Vector, a Fisher kernel based representation to describe a collection of images or the sequential frames of a video. We explore different generative models beyond the Gaussian Mixture Model as underlying probability distribution. First, the Student’s-t Mixture Model which captures the heavy tails of the small sample size of a visual stream. Second, Hidden Markov Models to explicitly capture the temporal ordering of the observations in a stream. For all our models we derive analytical approximations of the Fisher information matrix, which significantly improves recognition performance. We extensively evaluate the properties of our proposed method on three recent datasets for event recognition in photo collections and web videos, leading to an efficient compact visual stream representation which achieves state-of-the-art performance on all these datasets.
Dynamic Pricing and Markdown Timing Policies for Fashion Goods with Strategic Behaviour of Consumers

CURRENT SCIENCE, VOL. 116, NO. 10, 25 MAY 2019 1648 Yanli Fang, Xiangping Wang and Ping Fan are in the Department of Logistics Management and Engineering, Zhuhai College of Jilin University, Zhuhai, China; Weijing Wang is in the School of Business, Macao University of Science and Technology, Macao, China. *For correspondence. (e-mail: 280036340@qq.com) Dynamic pricing and markdown timing policies for fashion goods with strategic behaviour of consumers
Rayleigh wave attenuation with USArray

Xueyang Bao,1,∗ Colleen A. Dalton,1 Ge Jin,2 James B. Gaherty2 and Yang Shen3 1Earth, Environmental and Planetary Sciences, Brown University, 324 Brook Street, Providence RI 02912, USA. E-mail: xybao@uri.edu 2Lamont-Doherty Earth Observatory of Columbia University, 61 Route 9 W, Palisades, NY 10964, USA 3Graduate School of Oceanography, University of Rhode Island, 215 South Ferry Road, Narragansett, RI 02882, USA
How to Deal With Multi-Proxy Data for Paleoenvironmental Reconstructions: Applications to a Holocene Lake Sediment Record From the Tian Shan, Central Asia

Multi-proxy investigations on geological archives provide valuable information about environmental variations in the past. As opposed to single-proxy studies, the combination of several proxies can reveal more detailed information and strengthen subsequent paleoenvironmental reconstructions. However, there is still no consensus about how to deal with resulting highly dimensional datasets in a statistical manner. In many cases, the interpretations of multi-proxy datasets rely on visually matching several proxy records, which can lead to incorrect or insufficient interpretations. Here we report an innovative approach that combines the novel dimension reduction technique Uniform Manifold Approximation and Projection (UMAP) and the time series analysis R package asdetect to identify and characterize Holocene environmental phases and phase boundaries in a sediment core from Lake Chatyr Kol, southern Kyrgyzstan. Despite the fact that the Holocene climate evolution of Central Asia has been intensively studied during the last decades, knowledge about regional climate development during the Holocene and the underlying mechanisms is still relatively scarce. We particularly focus on phase transitions and differentiate between event-based shifts as opposed to gradual phase transitions. For this study, long-chain alkenones were used as a paleotemperature proxy and variations in long-chain alkyl diol distributions were ascribed to relative changes of algal input. The compound-specific stable hydrogen isotope compositions (δD) of individual n-alkanes were utilized as paleohydrological proxies, with the δD of mid-chain n-alkanes reflecting changes in the δD of the lake water and the δD of long-chain n-alkanes recording the δD of the meteoric water. We show the potential of modern analysis tools for data-driven paleoenvironmental reconstructions and advocate for their more frequent implementation in multi-proxy studies.
Multi-level conditional spectrum-based record selection for IDA

Incremental dynamic analysis (IDA) is widespread to evaluate the seismic response of structures. It employs one records set scaled to multiple intensity levels (IMLs) to estimate the structural response distribution. However, the dominating earthquake scenarios differ with the intensity, and a single set introduces bias that increases with scaling. The response is, however, better estimated using multiple stripe analysis (MSA) by selecting multiple hazard consistent record sets at different IMLs via, for example, conditional spectrum (CS) method. Still, IDA remains a popular tool, and would benefit from a single “good” set that would be more amenable to scaling with minimal bias. We explore alternatives of a “multi-level” CS (CSML) scheme, whereby the seismic properties of multiple IMLs are combined to derive a single set. Combined with advanced IMs, CSML provides a viable trade-off between the more accurate and complex method of CS–MSA versus the conceptually and practically simpler IDA.
Improving Nurse Anesthetist Intraoperative Handoff Process by Developing and Implementing an Evidence-Based, Facility-Specific Cognitive Aid

Miscommunication or non-transfer of pertinent patient information during intraoperative handoffs between anesthesia providers creates patient safety risks. An evidence-based facility-specific cognitive aid was developed and introduced to nurse anesthetists in an anesthesiology department of a large academic hospital with the aim of improving the intraoperative patient handoff process. The program used a handoff cognitive aid that addressed five pertinent patient information points. A secondary measure was evaluation of provider satisfaction. Twenty-four nurse anesthetists utilized the handoff cognitive aid during handoffs in the course of a 4-week pilot program. Eighty-eight nurse anesthetist handoffs were observed (23 with and 65 without the cognitive aid). Statistically significant improvement in the transmission of 3 of the 5 measured elements occurred when the cognitive aid was used. These areas included: intake and output (95.6% vs. 70.7%, p = 0.018); antibiotic administration (95.6% vs. 73.8%, p= 0.033); and intravenous access (100% vs. 76.9%, p = 0.009). An additional area that reached statistical significance (78.2% vs. 41.5%, p = 0.003) was the transmission of all 5 elements when the handoff cognitive aid was utilized in the handoff. In a postimplementation survey, nurse anesthetists utilizing the cognitive aid overwhelmingly agreed that the handoff cognitive aid was easy to use, contained appropriate content, and minimized risks to patient safety. Incorporation of a cognitive aid to standardize intraoperative handoffs was well received and improved communication of pertinent patient information during handoffs between nurse anesthetists.
DETECTION OF DIABETIC RETINOPATHY USING MINIMUM MEAN ABSOLUTE DEVIATION MODEL AND SUPPORT VECTOR MACHINE

This paper presents an automated system to analyze the retinal fundus image for the presence of diabetic retinopathy, which is one of the diseases that cause blindness if left unnoticed at their earliest stage. Diabetic retinopathy is asymptotic at their initial stages hence it is very difficult to identify them manually. So an automated system is designed, in which a retinal fundus image is fed to the system where it is subjected to various processes for the identification of diabetic retinopathy with high accuracy. Initially the image is subjected to pre-processing where the noises and other photographic artifacts are removed. Next, image segmentation is carried out to segment the area of interest. Although many segmentation algorithms have been designed earlier new algorithms are being proposed every day to improve the accuracy of segmentation and to decrease the computation time. MMAD model is used in this work to segment the lesion/exudates from the retinal images. In this model the 2D histogram of the preprocessed image is converted to the 1D histogram through diagonal projection and that is subject to the segmentation which produces the accurate result and the computational time is greatly reduced when compared to various other algorithms. The final stage in this system is lesion classification where the most important properties of the lesion are taken and given to the system. Support vector machine classifier is used to classify the lesion with higher accuracy and the performance of the proposed work is analysed with existing algorithms.
Bringing Research Evidence into Software Industry Practice A Study on Evidence-based Practice in the Software Industrial Setting

Research findings can influence decisions at many levels, but only if one knows how to translate them into actionable and practical information. One of the major concerns of empirical software engineering research is in making a real impact on software engineering practice, bridging the gap between academia and industry. The area calls for effective approaches to the dissemination of empirical evidence into practice and there are no simple answers for this problem. In this context, the main objective of this proposal is to develop a methodology to increase the influence of empirical results on software practices and project team behavior. The main contribution is to deepen relevant knowledge and experience on how to expand the use of empirical results in the software development process, including the selection and use of technologies and practices in software industry context.
A pilot study for diagnosis of genital Chlamydia trachomatis infections by polymerase chain reaction among symptomatic Indian women.

BACKGROUND Chlamydia trachomatis is the most common bacterial etiology of sexually transmitted infection. AIM A pilot study was designed using PCR for amplification and detection of a specific 517 bp sequence of the common endogenous plasmid of C. trachomatis from clinical swab specimens obtained from symptomatic female patients attending STD clinics of AIIMS and Regional STD Teaching, Training & Research Center, Safdarjang Hospital, New Delhi. METHODS 97 patients were recruited in the study, and endocervical swabs were collected following standard procedures. The samples were analyzed by PCR and direct fluorescence antibody (DFA) for detection of C. trachomatis, and the sensitivity, specificity, PPV and NPV of PCR were calculated taking DFA as gold standard. RESULTS Out of 97 samples tested, 9 were positive for C. trachomatis by PCR. 1 PCR positive patient was negative by DFA although a total of 11 patients were positive by DFA. The sensitivity, specificity, PPV and NPV of PCR with reference to DFA was 72.73%, 98.84%, 88.89% and 96.59%, respectively. This PCR had high specificity and NPV for detection of C.trachomatis. CONCLUSIONS In light of the introduction of enhanced syndromic approach, which involves the use of laboratory techniques (wherever possible) to confirm clinical diagnosis, a diagnostic PCR with high specificity and NPV is particularly valuable for determination of etiological diagnosis and hence contribute to judicious use of antimicrobials in the community.
Chapter 2 Chitin Metabolic Pathways in Insects and Their Regulation

Chitin, the matrix polymer of arthropod exoskeleton, occurs in three forms that have different structural and mechanical properties. In the insect cuticle and the peritrophic matrix, individual chitin chains are further organized into higher order structures that give chitinous matrices their unique and widely differing properties such as rigidity, elasticity and waterproofing. In this chapter, we review the biochemical pathways of chitin biosynthesis, degradation and modification. In many cases, there are multiple isozymes for carrying out each step of chitin metabolism with specialization among members of families of isozymes. The gene families encoding the enzymes of chitin metabolism and their regulation are presented. The roles of chitin metabolism isoenzymes within families as revealed by gene deletion studies or RNA interference are discussed. How the association of chitin with different assortments of proteins modifies the properties of chitin matrices is briefly outlined. S. Muthukrishnan (*) Department of Biochemistry & Molecular Biophysics, Kansas State University, 141 Chalmers Hall, Manhattan, KS 66506, USA e-mail: smk@ksu.edu H. Merzendorfer Department of Chemistry and Biology – Institute of Biology, University of Siegen, Adolf-Reichwein-Str. 2, 57076 Siegen, Germany e-mail: merzendorfer@chemie-bio.uni-siegen.de Y. Arakane Department of Applied Biology, Chonnam National University, Gwangju 61186, South Korea e-mail: arakane@chonnam.ac. kr Q. Yang School of Life Science and Biotechnology, Dalian University of Technology, No. 2 Linggong Road, Dalian 116024, China e-mail: qingyang@dlut.edu. cn
Drosophila switch gene Sex-lethal can bypass its switch-gene target transformer to regulate aspects of female behavior

Significance The Drosophila master sex-determination switch gene, Sex-lethal (Sxl), was thought to elicit all aspects of female-specific somatic differentiation other than size dimorphism by acting on the gene transformer (tra) alone. Here we show that at least one aspect of Drosophila female-specific behavior, ovulation, is controlled by Sxl acting developmentally on some target(s) other than tra in a small subset of neurons in which, surprisingly, the tra target gene fruitless may function also. This minor branch in the sex-determination pathway should be useful for understanding how genes control behavior and perhaps also how, during evolution, Sxl managed to usurp the role of tra as the master regulator of sex determination relatively quickly in Drosophila's insect ancestors. The switch gene Sex-lethal (Sxl) was thought to elicit all aspects of Drosophila female somatic differentiation other than size dimorphism by controlling only the switch gene transformer (tra). Here we show instead that Sxl controls an aspect of female sexual behavior by acting on a target other than or in addition to tra. We inferred the existence of this unknown Sxl target from the observation that a constitutively feminizing tra transgene that restores fertility to tra− females failed to restore fertility to Sxl-mutant females that were adult viable but functionally tra−. The sterility of these mutant females was caused by an ovulation failure. Because tra expression is not sufficient to render these Sxl-mutant females fertile, we refer to this pathway as the tra-insufficient feminization (TIF) branch of the sex-determination regulatory pathway. Using a transgene that conditionally expresses two Sxl feminizing isoforms, we find that the TIF branch is required developmentally for neurons that also sex-specifically express fruitless, a tra gene target controlling sexual behavior. Thus, in a subset of fruitless neurons, targets of the TIF and tra pathways appear to collaborate to control ovulation. In most insects, Sxl has no sex-specific functions, and tra, rather than Sxl, is both the target of the primary sex signal and the gene that maintains the female developmental commitment via positive autoregulation. The TIF pathway may represent an ancestral female-specific function acquired by Sxl in an early evolutionary step toward its becoming the regulator of tra in Drosophila.
A linear oscillator model predicts dynamic temporal attention and pupillary entrainment to rhythmic patterns

Rhythm is a ubiquitous feature of music that induces specific neural modes of processing. In this paper, we assess the potential of a stimulus-driven linear oscillator model (57) to predict dynamic attention to complex musical rhythms on an instant-by-instant basis. We use perceptual thresholds and pupillometry as attentional indices against which to test our model predictions. During a deviance detection task, participants listened to continuously looping, multiinstrument, rhythmic patterns, while being eye-tracked. Their task was to respond anytime they heard an increase in intensity (dB SPL). An adaptive thresholding algorithm adjusted deviant intensity at multiple probed temporal locations throughout each rhythmic stimulus. The oscillator model predicted participants’ perceptual thresholds for detecting deviants at probed locations, with a low temporal salience prediction corresponding to a high perceptual threshold and vice versa. A pupil dilation response was observed for all deviants. Notably, the pupil dilated even when participants did not report hearing a deviant. Maximum pupil size and resonator model output were significant predictors of whether a deviant was detected or missed on any given trial. Besides the evoked pupillary response to deviants, we also assessed the continuous pupillary signal to the rhythmic patterns. The pupil exhibited entrainment at prominent periodicities present in the stimuli and followed each of the different rhythmic patterns in a unique way. Overall, these results replicate previous studies using the linear oscillator model to predict dynamic attention to complex auditory scenes and extend the utility of the model to the prediction of neurophysiological signals, in this case the pupillary time course; however, we note that the amplitude envelope of the acoustic patterns may serve as a similarly useful predictor. To our knowledge, this is the first paper to show entrainment of pupil dynamics by demonstrating a phase relationship between musical stimuli and the pupillary signal.
An improved Genetic Algorithm For Fuzzy ... An improved Genetic Algorithm For Fuzzy Production PlanningProblems with Application

Production Planning or Master Production Schedule (MPS) is a key interface between marketing and manufacturing, since it links customer service directly to efficient use of production resources. Mismanagement of the MPS is considered as one of fundamental problem in operation and it can potentially lead to poor customer satisfaction. In this paper, an improved Genetic Algorithm (IGA) is used to solving fuzzy multi-objective master production schedule (FMOMPS). The main idea is to integrate GA with local search operator. The FMOMPS was applied in the Cotton and medical gauzes plant in Mosul city. The application involves determine the gross requirements by demand forecasting using artificial neural networks. The IGA proved its efficiency in solving MPS problems compared with the genetic algorithm for fuzzy and non-fuzzy model, as the results clearly showed the ability of IGA to determine intelligently how much, when, and where the additional capacities (overtimes) are required such that the inventory can be reduced without affecting customer service level. Keywords—Master Production Schedule; Fuzzy Model; Improved Genetic Algorithm; Multi-Objective Optimization.
Designing User Interfaces for Multi-Device Environments Master Thesis

Collaborative use of multiple interactive devices has become an increasing trend in everyday life. Yet, there is a lack of effective methods and tools to design user interfaces that target multi-device and multi-user environments. For now, most applications are designed for a specific device type and type of user. Iterations of the design and implementation are necessary to make the same user interface available for other device types and user roles. This makes the design of user interfaces for multi-device environments cumbersome and time-consuming. Also, keeping the design consistent across the different devices is an issue that is so far not handled sufficiently. This thesis presents XDStudio, a user interface editor, which addresses these issues and focuses on the design of distributed user interfaces in multi-device and multi-user environments. XDStudio aims to support both expert and non-expert users in designing the distribution of existing web-based user interfaces using two seamlessly connected design modes: a simulated mode, where the design and testing are realized in a central authoring device, and an on-device mode, where both a central device and the peripheral target devices are actively collaborating. XDStudio also offers an instant testing feature enabling the designer to check the distribution at any moment and return to the design process for further editing. A user study reveals interesting aspects regarding the usability of the tool, helps identify advantages and limitations of the two design modes and shows what kind of distribution scenarios and tasks are better performed in each design mode. The results of the user study finally enable us to propose improvements and areas of future work.