Miracle-dz/UniFAR-FTUs huggingface dataset:
Response to name: A dataset and a multimodal machine learning framework towards autism study

In this paper, we propose a “Response to Name Dataset” for autism spectrum disorder (ASD) study as well as a multimodal ASD auxiliary screening system based on machine learning. ASD children are characterized by their impaired interpersonal communication abilities and lack of response. In the proposed dataset, the reactions of children are recorded by cameras upon calling their names. The responsiveness of each child is then evaluated by a clinician with a score among 0, 1 and 2 following the Autism Diagnostic Observation Schedule (ADOS). We then develop a rule-based multimodal framework to quantitatively evaluate each child. Our system involves speech recognition based automatic name calling detection, face detection/alignment, head pose estimation, and considers the response speed, eye contact duration and head orientation to output the final prediction. Compared to existing work, our dataset characterizes a more precise and detailed scoring system with clinical trial standards, as well as a more spontaneous setting by incorporating less lab-controlled sessions with dynamic/cluttered environments, multi-pose mobile captured videos, and flexible number of accompanying adults. Experiments show that our machine predicted scores align closely with human professional diagnosis, showing promising potential in early screening of ASD, and shedding light on future clinical applications.
Topology-Varying Shape Matching and Modeling

The automatic creation of man-made 3D objects is an active area in computer graphics. Computer-assisted mixing and blending of components or subcomponents from existing example shapes can help users quickly produce interesting and creative designs. A key factor for automating this task is using algorithms that can match compatible parts between objects of different shape and structure. However, due to the coarse correspondence computed by current matching algorithms, automatic shape blending is mainly limited to the substitution of large compatible part sets. In this thesis, we address the problem of relating 3D shapes of different geometry and topology, with applications in shape synthesis. Our goal is to compute a fine-grained mapping between two shapes differing in the geometry, cardinality, and connectivity of their parts, and to use this mapping for continuous shape interpolation. First, we propose a framework for shape matching using a joint geometric and topological transformation. The framework follows the assumption that the best mapping for a pair of shapes is one that results from a shape transformation that minimally distorts the structural properties of a shape. We establish meaningful correspondences between shapes with large topological discrepancy by going beyond shape deformations and incorporating topological operations such as part split, duplication, and merging. We evaluate our correspondence algorithm on a diverse set of shape classes and compare the results to state-of-the-art methods. Second, we propose an algorithm for synthesizing interpolations between structurally different 3D shapes. Our algorithm produces a continuous and plausible shape transformation that gradually morphs the geometry of the individual parts, as well as performs any necessary topology-changing operations. We further demonstrate the utility of our framework by developing intuitive shape creation tools. We show how these tools can allow novice users to synthesize new 3D models from continuous blends of topologically different shapes.
Synergistic effect of entomopathogenic fungus Fusarium oxysporum extract in combination with temephos against three major mosquito vectors

Abstract Mosquito control using chemical insecticides is facing a major challenge due to development of insecticide resistance. Improving the efficiency of existing insecticides using synergistic secondary metabolites of biological origin is increasingly being researched. Herein, we evaluated the toxicity of Fusarium oxysporum extract alone and in binary combinations with temephos, on larvae and pupae of Anopheles stephensi, Aedes aegypti and Culex quinquefaciatus. F. oxysporum extract was characterized using TLC, FT-IR and GC-MS. After 24 h of exposure, the binary combination of temephos + F. oxysporum extract (1:1 ratio) was highly toxic to larvae of An. stephensi (LC50: 35.927 μg/ml), Ae. aegypti (LC50: 20.763 μg/ml) and Cx. quinquefasciatus, (LC50: 51.199 μg/ml). For pupae LC50 values were 38.668, 26.394, and 72.086 μg/ml, respectively. Histology studies of mosquitoes exposed to F. oxysporum extract showed vacuolation in epithelium, as well as in adipose, and muscle tissues of larval midgut. Overall, our results show that the synergistic combination of temephos and F. oxysporum extract is highly effective to control mosquito young instars.
Biology of Fibrous Composites: Development beyond the Cell Membrane

1. Defining the subject 2. The occurrence of fibrous composites 3. Properties of natural plywoods 4. Biomimickry: making liquid crystalline models of helicoids and other plywoods 5. How is fibre orientation controlled? 6. Unifying themes References Index.
DORNRÖSCHEN, DORNRÖSCHEN-LIKE, and PUCHI redundantly control floral meristem identity and organ initiation in Arabidopsis

The biphasic floral transition in Arabidopsis thaliana involves many redundant intersecting regulatory networks. The related AP2 transcription factors DORNRÖSCHEN (DRN), DORNRÖSCHEN-LIKE (DRNL), and PUCHI individually execute well-characterized functions in diverse developmental contexts, including floral development. Here, we show that their combined loss of function leads to synergistic floral phenotypes, including reduced floral merosity in all whorls, which reflects redundant functions of all three genes in organ initiation rather than outgrowth. Additional loss of BLADE-ON-PETIOLE1 (BOP1) and BOP2 functions results in the complete conversion of floral meristems into secondary inflorescence shoots, demonstrating that all five genes define an essential regulatory network for establishing floral meristem identity, and we show that their functions converge to regulate LEAFY expression. Thus, despite their largely discrete spatiotemporal expression domains in the inflorescence meristem and early floral meristem, PUCHI, DRN, and DRNL interdependently contribute to cellular fate decisions. Auxin might represent one potential non-cell-autonomous mediator of their gene functions, because PUCHI, DRN, and DRNL all interact with auxin transport and biosynthesis pathways.
Tumor necrosis factor-alpha and polycystic ovarian syndrome: a clinical, biochemical, and molecular genetic study.

BACKGROUND Tumor necrosis factor-alpha (TNF-α) appears to be linked with hyperandrogenism (HA), increased insulin resistance (IR), and obesity (Ob), which were common features noted with polycystic ovarian syndrome (PCOS). Our aim was to study the role of TNF-α in the pathogenesis of IR and Ob in PCOS, as well as a C850T (rs1799724) polymorphism in the promoter region of the TNF-α gene, in a group of 204 PCOS patients and 204 age-matched healthy controls. RESULTS Significant differences were observed between PCOS patients and controls. All the PCOS had elevated body mass index, waist circumference, waist-to-hip ratio, fasting insulin, homeostatic model assessment (HOMA) score, and serum TNF-α when compared with controls (p<0.05). Genotype distribution for the C-850T polymorphism was observed with the frequency of the variant T allele being 0% in the PCOS group and 9% in the control group (p=0.0032). CONCLUSIONS In conclusion, our present results suggest that the TNF-α system might contribute to the pathogenesis of HA, Ob, and IR in PCOS independent of a polymorphism of the TNF-α C850T (rs1799724) in our population.
Distributed model predictive control of bilinear HVAC systems using a convexification method

This paper proposes a distributed MPC strategy for bilinear HVAC systems with coupled dynamics and constraints. These couplings arise from the heat transfer between adjacent zones and the limited total supply energy and airflow rate. To handle the coupled dynamics and constraints, a decoupled method is needed for the distributed computation of the online MPC problem. Besides the coupling issue, the bilinear model is also a fundamental obstacle to efficient online computation. To solve this problem, a convex relaxation method is developed in this paper. The performance of the proposed MPC strategy is demonstrated by a numerical example.
Almost Optimal Channel Access in Multi-Hop Networks with Unknown Channel Variables

We consider the problem of online dynamic channel accessing in multi-hop cognitive radio networks. Previous works on online dynamic channel accessing mainly focus on single-hop networks that assume complete conflicts among all secondary users. In the multi-hop multi-channel network settings studied here, there is more general competition among different communication pairs. A simple application of models for single-hop case to multi-hop case with N nodes and M channels leads to exponential time/space complexity O (MN), and poor theoretical guarantee on throughput performance. We thus novelly formulate the problem as a linearly combinatorial multi-armed bandits (MAB) problem that involves a maximum weighted independent set (MWIS) problem with unknown weights. To efficiently address the problem, we propose a distributed channel access algorithm that can achieve 1/ρ of the optimum averaged throughput where each node has communication complexity O (r2+D) and space complexity O (m) in the learning process, and time complexity O (D mρr) in strategy decision process for an arbitrary wireless network. Here ρ = 1 + ε is the approximation ratio to MWIS for a local r-hop network with m <; N nodes, and D is the number of mini-rounds inside each round of strategy decision.
Spartan: A Distributed Array Framework with Smart Tiling

Application programmers in domains like machine learning, scientific computing, and computational biology are accustomed to using powerful, high productivity array languages such as MatLab, R and NumPy. Distributed array frameworks aim to scale array programs across machines. However, maximizing the locality of access to distributed arrays is an unsolved problem; such locality is critical for high performance. This paper presents Spartan, a distributed array framework that automatically determines how to best partition (aka "tile") n-dimensional arrays and to co-locate data with computation to maximize locality. Spartan combines a lazy-evaluation based, optimizing frontend with a distributed tiled array backend. Central to Spartan's design is a small number of carefully chosen parallel high-level operators, which form the expression graph captured by Spartan's frontend during runtime. These operators simplify the programming of distributed applications. More importantly, their well-defined semantics allow Spartan's runtime to calculate the costs of different tiling strategies and pick the best one for evaluating the entire expression graph. Using Spartan, we have implemented 12 applications from a variety of domains including machine learning and scientific computing. Our evaluations show that Spartan's automatic tiling mechanism leads to good and scalable performance while eliminating the need for manual tiling.
Taking into Account Sensory Knowledge: The Case of Geo-techologies for Children with Visual Impairments

This paper argues for designing geo-technologies supporting non-visual sensory knowledge. Sensory knowledge refers to the implicit and explicit knowledge guiding our uses of our senses to understand the world. To support our argument, we build on an 18 months field-study on geography classes for primary school children with visual impairments. Our findings show (1) a paradox in the use of non-visual sensory knowledge: described as fundamental to the geography curriculum, it is mostly kept out of school; (2) that accessible geo-technologies in the literature mainly focus on substituting vision with another modality, rather than enabling teachers to build on children's experiences; (3) the importance of the hearing sense in learning about space. We then introduce a probe, a wrist-worn device enabling children to record audio cues during field-trips. By giving importance to children's hearing skills, it modified existing practices and actors' opinions on non-visual sensory knowledge. We conclude by reflecting on design implications, and the role of technologies in valuing diverse ways of understanding the world.
English to Urdu Statistical Machine Translation: Establishing a Baseline

The aim of this paper is to categorize and present the existence of resources for Englishto-Urdu machine translation (MT) and to establish an empirical baseline for this task. By doing so, we hope to set up a common ground for MT research with Urdu to allow for a congruent progress in this field. We build baseline phrase-based MT (PBMT) and hierarchical MT systems and report the results on 3 official independent test sets. On all test sets, hierarchial MT significantly outperformed PBMT. The highest single-reference BLEU score is achieved by the hierarchical system and reaches 21.58% but this figure depends on the randomly selected test set. Our manual evaluation of 175 sentences suggests that in 45% of sentences, the hierarchical MT is ranked better than the PBMT output compared to 21% of sentences where PBMT wins, the rest being equal.
Unobtrusive Gait Recognition Using Smartwatches

Gait recognition is a technique that identifies or verifies people based upon their walking patterns. Smartwatches, which contain an accelerometer and gyroscope have recently been used to implement gait-based biometrics. However, this prior work relied upon data from single sessions for both training and testing, which is not realistic and can lead to overly optimistic performance results. This paper aims to remedy some of these problems by training and evaluating a smartwatch-based biometric system on data obtained from different days. Also, it proposes an advanced feature selection approach to identify optimal features for each user. Two experiments are presented under three different scenarios: Same-Day, Mixed-Day, and Cross-Day. Competitive results were achieved (best EERs of 0.13% and 3.12% by using the Same day data for accelerometer and gyroscope respectively and 0.69% and 7.97% for the same sensors under the Cross-Day evaluation. The results show that the technology is sufficiently capable and the signals captured sufficiently discriminative to be useful in performing gait recognition.
Differential Transcriptome Analysis of Early Postnatal Developing Longissimus Dorsi Muscle from Two Pig Breeds Characterized in Divergent Myofiber Traits and Fatness

ABSTRACT Meat quality traits (MQTs) are very important in the porcine industry, which are mainly determined by skeletal muscle fiber composition, extra-muscular and/or intramuscular fat content. To identify the differentially expressed candidate genes affecting the meat quality traits, first we compared the MQTs and skeletal muscle fiber characteristics in the longissimus dorsi muscle (LDM) of the Northeast Min pig (NM) and the Changbaishan wild boar (CW) with their body weight approaching 90 kg. The significant divergences in the skeletal muscle fiber phenotypes and fatness traits between the two porcine breeds established an ideal model system for further identifying potential key functional genes that dominated MQTs. Further, a transcriptome profile analysis was performed using the Illumina sequencing method in early postnatal developing LDM from the two breeds at the ages of 42 days. Comparative analysis between these two cDNA libraries showed that there were 17,653 and 22,049 unambiguous tag-mapped sense transcripts detected from NM and CW, respectively. 4522 differentially expressed genes (DEGs) were revealed between the two tissue samples, of them, 4176 genes were found as having been upregulated and 346 genes were identified as having been downregulated in the NM library. By pathway enrichment analysis, a set of significantly enriched pathways were identified for the DEGs, which are potentially involved in myofiber development, differentiation and growth, lipogenesis and lipolysis in porcine skeletal muscle. The expression levels of 30 out of the DEGs were validated by real-time quantitative reverse transcriptase PCR (qRT-PCR) and the observed result was consistent noticeably with the Illumina transcriptome profiles. The findings from this study can contribute to future investigations of skeletal muscle growth and development mechanism and to establishing molecular approaches to improve meat quality traits in pig breeding.
A Feminine Care Clinical Research Program Transforms Women’s Lives

Feminine hygiene products and menstruation education have transformed the lives of women throughout the world. The P&G Feminine Care Clinical Innovation Research Program has played a key role by expanding scientific knowledge as well as developing technical insights and tools for the development of feminine hygiene products. The aim has been to meet the needs of women throughout their life stages, advancing their urogenital health beyond just menstruation, as well as helping to understand the role of sex hormones in various important health issues that women face. This review article highlights key contributions and research findings in female hygiene products, urogenital health research, and method development. The clinical research team focused on utilizing the results of clinical safety studies to advance the acceptance of feminine hygiene products world-wide. Key findings include that perception of skin sensitivity is not limited to the facial area, but is also relevant to the body and the genital area. Also, they shed light on the role of estrogen in autoimmune diseases as well as premenstrual syndrome. Efforts in the method development area focused on innovative tools that are reliable, predictive of clinical trial results and capable of measuring wear comfort, genital skin health, and the impact of product use on the consumer’s quality of life. A novel method, behind-the-knee (BTK) test, developed to model irritation under normal wear conditions, was the first to account for both chemical and mechanical sources of irritation. The method has been accepted by the FDA as a substitute in clinical trials in some cases, and by American Society for Testing and Materials as a global standard test method. Additional proprietary methods were developed to enhance visual grading of irritation using cross-polarized light, to measure the amount of lotion transferred from sanitary pads, and to evaluate the skin mildness. Finally, the Farage Quality of Life tool was created to measure consumer’s well-being. Based on the results of this extensive clinical research and the newly developed testing methods, the changing needs of women throughout their life stages are better met.
Adaptive control for quadrotors

This paper presents an indirect adaptive control methodology for quadorotors. The methodology aims at controlling a family of quadrotor micro air vehicle with a common set of sensors and processing hardware but with various sizes, configurations, payloads and propeller types. The parameter estimation is based on the Recursive Least Square algorithm which feeds the estimates to a linear parameter varying controller. The synthesis of the controller relies on structured H∞ algorithm.
Internal Collusive Eavesdropping of Interference Alignment Networks

Interference alignment (IA) networks seem secure, due to the fact that signals from the legitimate network may act as interference to disrupt the external eavesdropping. However, when some users inside the network are cooperating to eavesdrop one certain user, it will not be secure any longer. Thus, we concentrate on the eavesdropping attacks in this paper, and propose a novel collusive eavesdropping scheme (CES) in a K- user IA network, where one of the users is eavesdropped by an eavesdropper with the aid of the other (K-2) cooperators. To perform the passive eavesdropping without being noticed by the targeted user, the precoding and decoding matrices of the eavesdropper and cooperators are re-designed, and some of the cooperators should sacrifice their own quality of transmission to help the eavesdropper meet the feasibility condition. Extensive simulation results are provided to show the eavesdropping effectiveness of the proposed CES in IA networks.
Identifying Differences Between Cut Marks Made on Bone by a Machete and Katana: A Pilot Study

The aim of this research was to identify characteristics specific to a machete and katana on three different bone types. One machete and two katanas were used to produce cut marks on Sus scrofa rib, flat and long bones. Fifty‐nine cuts were produced by the katanas and 38 by the machete. The presence of flaking, feathering, peeling, micropeeling, chattering, microcurvature, scoop defect, and exit notch was noted, and bivariate associations between each characteristic and weapon type were assessed using Pearson's chi‐square tests for independence and logistic regression models developed. Significant predictors for machete cut marks are scoop defect for rib bones (correct classification 93%), micropeeling in flat bones, chattering on flat and long bones (all p < 001) and for the katana, microcurvature (p < 004) and exit notch on flat and long bones (p < 001; correct classification 96% and 100%, respectively). The identified bivariate associations and final logistic regression models may be utilized in forensic investigations when identifying hacking trauma.
Initial preference for drinking goal in the treatment of alcohol problems: I. Baseline differences between abstinence and non-abstinence groups.

AIMS To compare baseline characteristics of clients initially preferring abstinence with those preferring non-abstinence at the screening stage of a randomized controlled trial of treatment for alcohol problems (UKATT) and to identify predictors of goal preference from client characteristics present before the preference was stated. METHODS From discussions with clients entering the trial (N = 742), screeners noted whether clients were aiming for abstinence 'probably yes' or 'probably no'. Differences between the two groups thus formed were explored by univariate comparisons among client characteristics recorded at baseline assessment and by logistic regression analysis with pre-existing characteristics as independent variables. RESULTS Across all UKATT sites, 54.3% of clients expressed a preference for abstinence and 45.7% for non-abstinence. In univariate comparisons, clients preferring abstinence were significantly (P < 0.01) more likely to: (i) be female, (ii) be unemployed, (iii) report drinking more heavily but less frequently, (iv) have been detoxified in the 2 weeks prior to assessment, (v) report more alcohol problems, (vi) be in the action stage of change, (vii) report greater negative expectancies of drinking, (viii) report greater mental and physical ill-health, (ix) report less social support for drinking and (x) be more confident of their ability to resist heavy drinking in tempting situations. In the logistic regression model, the strongest predictors of goal preference were gender, drinking pattern, recent detoxification and social support for drinking. CONCLUSION The implications of these findings for service delivery are best considered in conjunction with findings from a companion paper reporting treatment outcomes associated with each goal preference.