Miracle-dz/UniFAR-FTUs huggingface dataset:
Refining an Asynchronous Telerehabilitation Platform for Speech-Language Pathology: Engaging End-Users in the Process

Asynchronous telerehabilitation in which computer-based interventions are remotely monitored and adapted offline is an emerging service delivery model in the rehabilitation of communication disorders. The asynchronous nature of this model may hold a benefit over its synchronous counterpart by eliminating scheduling issues and thus improving efficiency in a healthcare landscape of constrained resource allocation. The design of asynchronous telerehabilitation platforms should therefore ensure efficiency and flexibility. The authors have been engaged in a program of research to develop and evaluate an asynchronous telerehabilitation platform for use in speech-language pathology. eSALT is a novel asynchronous telerehabilitation platform in which clinicians design and individualize therapy tasks for transfer to a client's mobile device. An inbuilt telerehabilitation module allows for remote monitoring and updating of tasks. This paper introduces eSALT and reports outcomes from an usability study that considered the needs of two end-user groups, people with aphasia and clinicians, in the on-going refinement of eSALT. In the study participants with aphasia were paired with clinicians who used eSALT to design and customize therapy tasks. After training on the mobile device the participants engaged in therapy at home for a period of 3 weeks, while clinicians remotely monitored and updated tasks. Following the home trial, participants, and clinicians engaged in semi-structured interviews and completed surveys on the usability of eSALT and their satisfaction with the platform. Content analysis of data involving five participants and three clinicians revealed a number of usability themes including ease of use, user support, satisfaction, limitations, and potential improvements. These findings were translated into a number of refinements of the eSALT platform including the development of a client interface for use on the Apple iPad®, greater variety in feedback options to both the participant and clinician, automatic transfer of results to the clinician, and expansion of the task template list. This research highlights the importance of including end-users in the process of technology refinement, in order to ensure effective and efficient use of the technology. Future directions for research are discussed including clinical trials in which the effectiveness of and adherence to intervention protocols using asynchronous telerehabilitation are examined.
The association between impulsivity and sensory processing patterns in healthy adults

Introduction Growing evidence suggests that an individual's style of processing sensory information plays a role in affective disorders. However, most of this work focuses on the relationship between sensory hypersensitivity and factors related to internalizing disorders. This study explores the association between sensory processing styles and impulsivity, a fundamental feature of externalizing disorders, in healthy adults. Method Two hundred and twenty-six healthy individuals aged 18–60 years completed the adolescent/adult sensory profile, Barratt impulsiveness scale, and a computerized response inhibition task (go/no-go task). Findings Low registration sensory processing scores were positively correlated with Barratt impulsivity scores. In addition, individuals high in low registration were more likely to meet criteria for high impulsivity. Individuals higher in sensory sensitivity made more impulsive errors on the response inhibition task. Conclusion The findings suggest that individuals with low registration are more impulsive. When helping clients manage impulsivity, occupational therapists should consider their sensory processing patterns and utilize interventions that address sensory needs. Future studies should examine these associations in clinical populations characterized by high rates of impulsive behavior.
Partitioning nuclear and chloroplast variation at multiple spatial scales in the neotropical epiphytic orchid, Laelia rubescens

Insights into processes that lead to the distribution of genetic variation within plant species require recognition of the importance of both pollen and seed movement. Here we investigate the contributions of pollen and seed movement to overall gene flow in the Central American epiphytic orchid, Laelia rubescens. Genetic diversity and structure were examined at multiple spatial scales in the tropical dry forest of Costa Rica using nuclear (allozymes) and chloroplast restriction fragment length polymorphism (RFLP) markers, which were found to be diverse (allozymes, P = 73.3%; HE = 0.174; cpDNA, HE = 0.741). Nuclear genetic structure (FSTn) was low at every spatial scale (0.005–0.091). Chloroplast markers displayed more structure (0.073–0.254) but relatively similar patterns. Neither genome displayed significant isolation‐by‐distance. Pollen and seed dispersal rates did not differ significantly from one another (mp/ms = 1.40) at the broadest geographical scale, among sites throughout Costa Rica. However, relative contributions of pollen and seeds to gene flow were scale‐dependent, with different mechanisms determining the dominant mode of gene flow at different spatial scales. Much seed dispersal is highly localized within the maternal population, while some seeds enter the air column and are dispersed over considerable distances. At the intermediate scale (10s to 100s of metres) pollinators are responsible for substantial pollen flow. This species appears capable of distributing its genes across the anthropogenically altered landscape that now characterizes its Costa Rican dry forest habitat.
Multi-modal scene understanding using probabilistic models

This thesis addresses the problem of relating spoken utterances to the simultaneously perceived visual scene context. The development of systems that integrate verbal and visual information is an extending field of research. It is pushed by various applications like the indexing and querying of video databases, service robotics, augmented reality, document analysis, documentation systems with multi-modal interfaces, or other multi-media systems. Each of these applications has to relate two or more different input modalities, which is also known as the correspondence problem. The task of relating realistic inputs like speech or images is complicated by the fact that the interpretations of the surface modalities are often erroneous or incomplete such that an integration component must consider noisy and partial interpretations. As a consequence, this thesis treats the correspondence problem as a probabilistic decoding process. This perspective distinguishes this approach from other approaches that propose rule-based translation schemes or integrated knowledge bases and assume that a visual representation can be logically transformed into a verbal representation and vice versa. This thesis successfully applies Bayesian networks to the task of integrating speech and images. The correspondence problem is solved in the language of Bayesian networks in a consistent and efficient way by using a novel combination of conditioning and elimination techniques. The experimental study identifies Bayesian networks as an adequate formalism for speech and image integration tasks. The mental models of the speaker are partially reconstructed by estimating conditional probabilities from the data of psycholinguistic experiments. Context dependent shifts of word meanings are modeled by the structure of the network. The proposed Bayesian network scheme for integrating multi-modal input has been applied to a construction scenario. A robot is instructed by a speaker to grasp objects from a table, join them together, and put them down again. In this thesis an integration component is realized that is able to identify objects in the visual scene that are verbally referred to by the speaker. This task is successfully performed despite of vague descriptions, erroneous recognition results, and the use of names with unknown semantics. Several interaction tasks have been implemented that perform multi-modal object recognition, link unknown object names to scene objects, disambiguate alternative interpretations of utterances, predict undetected mounting relations, or determine the selected reference frame of the speaker.
Effects of sodium arsenate and arsenite on male reproductive functions in Wistar rats

ABSTRACT Arsenic (As), in the form of trivalent arsenite or pentavalent arsenate, is a ubiquitous toxic compound naturally occurring in the environment. This study aimed to evaluate the impact of two different forms of inorganic As on reproductive parameters following oral exposure. Adult Wistar male rats were exposed to sodium arsenite or arsenate at concentrations of 0.01 mg/L or 10 mg/L for 56 d in drinking water. Sodium arsenite at both concentrations and sodium arsenate at 10 mg/L produced reduction in daily sperm production, in number of spermatids in the testis, and in sperm in the epididymal caput/corpus regions. Changes in epididymal morphometry were variable and region specific. Total and progressive sperm motility and sperm morphology did not differ markedly between controls and animals exposed to As. The body and reproductive organs weights, as well as testosterone concentration, remained unchanged among all groups. In conclusion, As exposure in drinking water over 56 d produced damage in male reproductive functions in adult rats, suggesting that fertility problems might occur. Therefore, additional studies need to be undertaken to investigate potential mechanisms underlying sodium arsenite- and arsenate-induced disturbances in fertility and reproductive performance.
Response: Organizations Are Not Central Tendencies: Shadowboxing in the Dark, Round 2

The article presents a response by William H. Glick to a commentary on his paper “Conceptualizing and measuring organizational and psychological climate: Pitfalls in multilevel research. ” Glick notes the differences in definitions of organizational climate (OC). One definition classifies OC as a psychological construct, the other defines it as an organizational attribute. He acknowledges that the alternate viewpoints help to identify fundamental differences between two schools of thought in organizational science.
A REVIEW PAPER ON FACE RECOGNITION TECHNIQUE

Face recognition has been a fast growing, challenging and interesting area in real time applications. A large number of face recognition algorithms have been developed in last decades. In this paper an attempt is made to review a wide range of methods used for face recognition comprehensively. This include PCA, LDA, ICA, SVM, Gabor wavelet soft computing tool like ANN for recognition and various hybrid combination of this techniques. This review investigates all these methods with parameters that challenges face recognition like illumination, pose variation, facial expressions. Index Terms
Compressed Progressive Meshes

Most systems that support visual interaction with 3D models use shape representations based on triangle meshes. The size of these representations imposes limits on applications for which complex 3D models must be accessed remotely. Techniques for simplifying and compressing 3D models reduce the transmission time. Multiresolution formats provide quick access to a crude model and then refine it progressively. Unfortunately, compared to the best nonprogressive compression methods, previously proposed progressive refinement techniques impose a significant overhead when the full resolution model must be downloaded. The CPM (compressed progressive meshes) approach proposed here eliminates this overhead. It uses a new technique, which refines the topology of the mesh in batches, which each increase the number of vertices by up to 50 percent. Less than an amortized total of 4 bits per triangle encode where and how the topological refinements should be applied. We estimate the position of new vertices from the positions of their topological neighbors in the less refined mesh using a new estimator that leads to representations of vertex coordinates that are 50 percent more compact than previously reported progressive geometry compression techniques.
The Keck Planet Search: Detectability and the Minimum Mass and Orbital Period Distribution of Extrasolar Planets

We analyze 8 years of precise radial velocity measurements from the Keck Planet Search, characterizing the detection threshold, selection effects, and completeness of the survey. We first carry out a systematic search for planets, by assessing the false-alarm probability associated with Keplerian orbit fits to the data. This allows us to understand the detection threshold for each star in terms of the number and time baseline of the observations, and the underlying “noise” from measurement errors, intrinsic stellar jitter, or additional low-mass planets. We show that all planets with orbital periods P < 2000 days, velocity amplitudes K > 20 m s-1, and eccentricities e ≲ 0.6 have been announced, and we summarize the candidates at lower amplitudes and longer orbital periods. For the remaining stars, we calculate upper limits on the velocity amplitude of a companion. For orbital periods less than the duration of the observations, these are typically 10 m s-1 and increase ∝ P2 for longer periods. We then use the nondetections to derive completeness corrections at low amplitudes and long orbital periods and discuss the resulting distribution of minimum mass and orbital period. We give the fraction of stars with a planet as a function of minimum mass and orbital period and extrapolate to long-period orbits and low planet masses. A power-law fit for planet masses >0.3 MJ and periods < 2000 days gives a mass-period distribution dN = CMα Pβ d ln Md ln P with α = -0.31 ± 0.2, β = 0.26 ± 0.1, and the normalization constant C such that 10.5% of solar type stars have a planet with mass in the range 0.3–10 MJ and orbital period 2–2000 days. The orbital period distribution shows an increase in the planet fraction by a factor of ≈5 for orbital periods ≳300 days. Extrapolation gives 17%–20% of stars having gas giant planets within 20 AU. Finally, we constrain the occurrence rate of planets orbiting M dwarfs compared to FGK dwarfs, taking into account differences in detectability.
America's Changing Farmscape: A Study of Agricultural Tourism in Michigan*

Abstract Agricultural tourism incorporates visits to farms for the purposes of on-site retail purchases, enjoyment, and education. Long popular in the European Union (EU), agritourism is gaining popularity throughout the United States. Interest has grown as a result of stagnant grain prices, rising farm costs, and growing international competition. For rural areas seeking new economic options, the potential of these operations to generate new sources of income through sales and horizontal linkages to other tourism-based activities has sparked interest beyond the farm gate. This article, based on a survey and a statistical analysis of 300 agritourism operations in Michigan, summarizes factors associated with successful operations.
A Toeplitz Covariance Matrix Reconstruction Approach for Direction-of-Arrival Estimation

It is known that there exist two kinds of methods for direction-of-arrival (DOA) estimation in the literature: the subspace-based method and the sparsity-based method. However, pervious works reveal that the former method cannot address the case in which the number of signals is larger than that of sensors, whereas the latter one always suffers from the influence of basis mismatch. In this paper, to overcome these two shortcomings, we propose a new method called covariance matrix reconstruction approach (CMRA) for both uniform linear array and sparse linear array. In particular, by exploiting the Toeplitz structure of the covariance matrix of the array output, we formulate a low-rank matrix reconstruction (LRMR) problem for covariance matrix recovery. The nonconvex LRMR problem is then relaxed by replacing the rank norm with the nuclear norm and solved using the optimization toolbox. Next, we retrieve the DOAs from the recovered covariance matrix by using the subspace-based methods and obtain an estimated number of signals as a byproduct. We also provide two algorithm implementations for the LRMR problem based on duality and alternating direction method of multipliers, respectively. It is shown that CMRA can be regarded as an atomic norm minimization model or a gridless version of the sparsity-based methods and can recover more signals than sensors with a well-designed array. Numerical experiments are provided to validate the effectiveness of the proposed method, in comparison with some of the existing methods.
NMRmix: A Tool for the Optimization of Compound Mixtures in 1D 1H NMR Ligand Affinity Screens

NMR ligand affinity screening is a powerful technique that is routinely used in drug discovery or functional genomics to directly detect protein–ligand binding events. Binding events can be identified by monitoring differences in the 1D 1H NMR spectrum of a compound with and without protein. Although a single NMR spectrum can be collected within a short period (2—10 min per sample), one-by-one screening of a protein against a library of hundreds or thousands of compounds requires a large amount of spectrometer time and a large quantity of protein. Therefore, compounds are usually evaluated in mixtures ranging in size from 3 to 20 compounds to improve the efficiency of these screens in both time and material. Ideally, the NMR signals from individual compounds in the mixture should not overlap so that spectral changes can be associated with a particular compound. We have developed a software tool, NMRmix, to assist in creating ideal mixtures from a large panel of compounds with known chemical shifts. Input to NMRmix consists of an 1H NMR peak list for each compound, a user-defined overlap threshold, and additional user-defined parameters if default settings are not used. NMRmix utilizes a simulated annealing algorithm to optimize the composition of the mixtures to minimize spectral peak overlaps so that each compound in the mixture is represented by a maximum number of nonoverlapping chemical shifts. A built-in graphical user interface simplifies data import and visual evaluation of the results.
Technology Usage and Sales Teams: A Multilevel Analysis of the Antecedents of Usage

Extensive research has investigated the antecedents and impact of adoption of technology in the sales force. Interestingly, even though sales teams have proliferated, most research on adoption to date is at the individual level of analysis. Therefore, we conduct research of individual and team characteristics and their influence on technology adoption through a multilevel analysis of adoption. We use survey data from 673 salespeople at a pharmaceutical firm distributed among 224 sales teams who reported to 122 external managers. Our results validate the importance of investigating relationships at multiple levels. Specific effects from individual experience, which is important within the typical individual analysis, did not have an impact within our study. Instead, the average experience of the team was a stronger antecedent to adoption within a sales team. The strong effect of peer usage of technology within a team compels us to recommend that managers create teams that include users with strong computer self-efficacy in order to accelerate adoption by those less inclined to adopt. Also, team adoption was strengthened by sales teams who accepted the goals of committed management. However, both empowerment of teams by management and team potency had a significant negative effect on adoption.
The STAT5–GATA2 Pathway Is Critical in Basophil and Mast Cell Differentiation and Maintenance

Transcription factor GATA binding protein 2 (GATA2) plays critical roles in hematopoietic stem cell survival and proliferation, granulocyte–monocyte progenitor differentiation, and basophil and mast cell differentiation. However, precise roles of GATA2 in basophil and mast cell differentiation and maintenance have not been delineated. We have identified GATA2 as an essential transcription factor in differentiation of newly identified common basophil and mast cell progenitors into basophils and mast cells. We observed Gata2 haploinsufficiency for mast cell differentiation, but not for basophil differentiation. We examined the precise role of GATA2 in maintaining the expression of a wide range of genes that are important for performing basophil or mast cell functions. The effects of GATA2 on gene expression were broadly based. We demonstrated that GATA2 was required for maintaining Fcer1a mRNA and FcεRIα protein expression on both basophils and mast cells, as well as for maintaining Kit mRNA and c-Kit protein expression on mast cells. GATA2 was required for histamine synthesis and was also critical for Il4 mRNA expression in basophils and Il13 mRNA expression in mast cells. We demonstrate a STAT5–GATA2 connection, showing that the STAT5 transcription factor directly bound to the promoter and an intronic region of the Gata2 gene. Overexpression of the Gata2 gene was sufficient to direct basophil and mast cell differentiation in the absence of the Stat5 gene. Our study reveals that the STAT5–GATA2 pathway is critical for basophil and mast cell differentiation and maintenance.
Enhancing a Short Measure of Big Five Personality Traits With Bayesian Scaling

A study in a university clinic/laboratory investigated adaptive Bayesian scaling as a supplement to interpretation of scores on the Mini-IPIP. A “probability of belonging” in categories of low, medium, or high on each of the Big Five traits was calculated after each item response and continued until all items had been used or until a predetermined criteria for the posterior probability has been obtained. The study found higher levels of correspondence with the IPIP-50 score categories using the adaptive Bayesian scaling than with the Mini-IPIP alone. The number of additional items ranged from a mean of 2.9 to 12.5 contingent on the level of certainty desired.
Psychometric Properties of the Resiliency Scales for Children and Adolescents and Use for Youth With Psychiatric Disorders

This study examines psychometric properties of the Resiliency Scales for Children and Adolescents (RSCA) in two clinical samples: one child sample (n = 110) and one adolescent sample (n = 178). The purpose of the study was to examine the distribution characteristics and internal consistency of RSCA scale, subscale, and index scores for youth who were diagnosed with various psychiatric disorders. This article expands on research reported in the RSCA technical manual, which examined small diagnostic groups by combining these groups when examination required larger samples. Findings suggest that the variability, apparent normal distribution, and good to excellent internal consistency of the RSCA global scale and index scores in these two clinical samples support their use to examine dimensions of normal development in clinical samples as well as in normative samples. Suggestions for future research are provided.
Optimizing Human Motion for the Control of a Humanoid Robot

Using pre-recorded human motion and trajectory tracking , we can control the motion of a humanoid robot for free-space, upper body gestures. However, the number of degrees of freedom, range of joint motion, and achievable joint velocities of today's humanoid robots are far more limited than those of the average human subject. In this paper, we explore a set of techniques for limiting human motion of upper body gestures to that achievable by a Sarcos humanoid robot located at ATR. In particular we have found that it is important to preserve the configuration of the hands and head for upper body motion. We assess the quality of the results by comparing the motion of the human actor to that of the robot, both visually and quantitatively.