Miracle-dz/UniFAR-FTUs huggingface dataset:
Actual vs. perceived exertion during active virtual reality game exercise

Background Virtual exercise has become more common as emerging and converging technologies make active virtual reality games (AVRGs) a viable mode of exercise for health and fitness. Our lab has previously shown that AVRGs can elicit moderate to vigorous exercise intensities that meet recommended health benefit guidelines. Dissociative attentional focuses during AVRG gameplay have the potential to widen the gap between participants' perception of exertion and actual exertion. Objective The aim of this study was to determine actual exertion (AEx) vs. perceived exertion (PEx) levels during AVRGs by measuring heart rate (HR) and ratings of perceived exertion (RPE) in two different settings. Materials and methods HR and RPE were collected on participants (N = 32; age 22.6 ± 2.6) during 10 min of gameplay in LabS and GymS using the HTC VIVE with the following games played: Fruit Ninja VR (FNVR), Beat Saber (BS), and Holopoint (HP). Results Participants exhibited significantly higher levels of AEx compared to reported PEx for all three AVRGs (Intensity): FNVR [AEx = 11.6 ± 1.8 (Light), PEx = 9.0 ± 2.0 (Very Light)], BS [AEx = 11.3 ± 1.7 (Light), PEx = 10.3 ± 2.1 (Very Light)], HP [AEx = 13.1 ± 2.3 (Somewhat Hard), PEx = 12.3 ± 2.4 (Light–Somewhat Hard)]. Additionally, participants playing in the GymS experienced significantly higher levels of AEx [12.4 ± 2.3 (Light–Somewhat Hard)] and PEx [10.8 ± 2.5 (Very Light–Light)] compared to the LabS [AEx = 11.6 ± 1.8 (Light), PEx = 10.3 ± 2.6 (Very Light–Light)]. Conclusion Perceptions of exertion may be lower than actual exertion during AVRG gameplay, and exertion levels can be influenced by the setting in which AVRGs are played. This may inform VR developers and health clinicians who aim to incorporate exercise/fitness regimens into upcoming ‘virtual worlds' currently being developed at large scales (i.e., the “metaverse”).
Investigating the use of duration‐based windows and estimation by analogy for COCOMO

In model‐based software estimation, using the right training data is a key contributor for making accurate predictions, which is crucial for the success of software projects. This study investigates the use of duration‐based windows and estimation by analogy to calibrate COCOMO and assess their estimation performance. We compare these approaches as well as the use of all available historical data using the COCOMO data set of 341 projects and NASA data set of 93 projects. The results show that timing information exists in the data sets affecting estimation accuracy. Given sufficient data for calibration, using recently completed projects within short durations generates more accurate estimates than retaining all historical data or using k‐nearest neighbors based on estimation by analogy. More training data spanning a long period of time may not lead to improved estimation accuracy. This study offers evidence to support the use of projects completed within recent years for training estimation models.
Hormonal Regulation of Semaphorin 7a in ER+ Breast Cancer Drives Therapeutic Resistance

SEMA7A predicts for and likely contributes to poor response to standard-of-care therapies, suggesting that patients with SEMA7A+ER+ tumors may benefit from alternative therapeutic strategies. Approximately 70% of all breast cancers are estrogen receptor–positive (ER+ breast cancer), and endocrine therapy has improved survival for patients with ER+ breast cancer. However, up to half of these tumors recur within 20 years. Recurrent ER+ breast cancers develop resistance to endocrine therapy; thus, novel targets are needed to treat recurrent ER+ breast cancer. Here we report that semaphorin 7A (SEMA7A) confers significantly decreased patient survival rates in ER+ breast cancer. SEMA7A was hormonally regulated in ER+ breast cancer, but its expression did not uniformly decrease with antiestrogen treatments. Additionally, overexpression of SEMA7A in ER+ cell lines drove increased in vitro growth in the presence of estrogen deprivation, tamoxifen, and fulvestrant. In vivo, SEMA7A conferred primary tumor resistance to fulvestrant and induced lung metastases. Prosurvival signaling was identified as a therapeutic vulnerability of ER+SEMA7A+ tumors. We therefore propose that targeting this pathway with inhibitors of survival signaling such as venetoclax may prove efficacious for treating SEMA7A+ tumors. Significance: SEMA7A predicts for and likely contributes to poor response to standard-of-care therapies, suggesting that patients with SEMA7A+ER+ tumors may benefit from alternative therapeutic strategies. Graphical Abstract: http://cancerres.aacrjournals. org/content/canres/81/1/187/F1.large. jpg. Graphical Abstract
Perceived barriers in accessing sexual and reproductive health services for youth in Lao People’s Democratic Republic

Background Sexual activity during youth is common in Lao PDR. However, young people seldom utilize sexual and reproductive health services and subsequently suffer from poor sexual and reproductive health. The aim of this qualitative study was to explore the barriers perceived by youth that prevent their access to sexual and reproductive health services. Methods Twenty-nine semi-structured interviews were conducted with 22 participants aged 15-25 years, from urban and rural areas. A vignette was used during interviews with those who had no experience with sexual and reproductive health services. Additionally, seven semi-structured interviews were conducted with health providers from youth-friendly health clinics and from public sexual and reproductive health services. Data were analyzed using a thematic approach. Results The main barriers preventing young people from accessing sexual and reproductive health services were related to cognitive accessibility and psychosocial accessibility. The cognitive accessibility barriers were a lack of sexual knowledge and a lack of awareness of services. Perceived barriers in psychosocial accessibility were the feelings of shyness and shame caused by negative cultural attitudes to premarital sex, and the fear of parents finding out about visits to public sexual and reproductive health services, due to lack of confidentiality in the services and among health providers. In addition, the barriers of geographical accessibility, mainly insufficient availability of youth-friendly health clinics. Conclusion To improve access to services, a multi-component strategy is needed: promotion of youth-friendly health clinics; sexual education in schools; a formal referral system between schools and youth-friendly health clinics; and community support interventions. Prior to implementation, more research should be done on the applicability of these methods in the Laos context. Future research should try to determine the cost-effectiveness of youth-friendly health clinics integrated in a district hospital and stand-alone clinics, to provide insight into which form should be further developed.
Real‐time quality authentication of honey using atmospheric pressure chemical ionisation mass spectrometry (
 APCI
 ‐
 MS
 )

The aim of this study was to use gas chromatography‐mass spectrometry (GC‐MS) and APCI‐MS techniques to detect adulteration in honey. The key volatile compounds in the headspace of the adulterated honey were marked by GC‐MS and their representative fragment ions were utilised in scanning honey samples using the real‐time APCI‐MS system. The PLS models validated using independent data sets resulted in coefficient of the determination (Rp2) of 0.97 and 0.96 and root mean square error in prediction (RMSEP) of 2.62 and 2.45 for the GC‐MS and APCI‐MS data sets respectively. The most efficient volatiles from GC‐MS analysis and their corresponding fragment ions m/z from APCI‐MS data analysis were then identified and used to develop new PLS models to predict the level of adulteration. The best PLS model gave Rp2 of 0.95 and RMEP of 2.60% in the independent validation set indicating that the model was very accurate in predicting the level of adulteration.
Preparing for Renovation: Estimating Shelf Occupancy to Inform Decision Making Regarding the Redevelopment of Library Space

ABSTRACT University Library at Indiana University-Purdue University Indianapolis is in the process of repurposing space currently occupied by the print collection. To prepare for further reallocation of library space, reliable estimates of stacks space were needed. Two members of the Access Services Team applied systematic random sampling to estimate existing—and anticipated—empty shelf space. Results indicate that more than 30% of the shelf space is empty, while over 25% is occupied by journals, most of which are available in electronic format. These estimates would be used to inform decision making about shifting and/or withdrawal of library materials in preparation for the renovation of additional library spaces. The data-gathering process as well as data analysis and application used during the project may be applicable in other academic libraries.
The Therapeutic Use of Clay

This article is a descriptive account of using clay within the setting of a psychiatric day unit. It is Intended to act as a working guide for therapists who may be interested in setting up a similar group. The group has changed from a craft group to a therapeutic assessment and treatment group. Two case examples are provided, and the effectiveness of such a group and the types of client who may benefit are discussed briefly.
Evaluation of a World Wide Web-Based Graduate Social Work Research Methods Course

SUMMARY This paper reports on the evaluation of a world-wide-web-based social work research methods course in experimental design. The course was taught entirely on the Internet, with no meetings on campus. The same instructor taught another section of the same course during the same semester on campus. Descriptive process data and comparative student outcome data (grades and satisfaction) are presented. Recommendations are made for others considering such courses.
A complex ray approach to the acoustics of fluid-loaded structures

This thesis provides a geometrical asymptotic approach to some fluid-loading pro­blems in acoustics.The first half concerns the bulk wave insonification of flat fluid-loaded membranes and elastic solids. Particular attention is paid to the excitation of the leaky surface wave of these configurations, with a new geometrical interpretation, using complex rays, of the displacement of the cut-off angle from the Mach angle given. The types of bulk wave insonification considered are cylindrical and spherical waves and Gaussian beam incidence, and all these fields are described in terms of complex rays.The second half concerns the bulk wave insonification of convex fluid-loaded boun­daries. Specifically the impedance and membrane boundaries are considered un­dergoing plane wave incidence. Unlike the flat boundary problems considered, the plane wave can excite surface waves and this is considered. Finally, the asymptotic field produced when a ray is tangentially incident to a soft convex boundary, thus exciting a creeping wave, is obtained.
An Approach to Mitigate Line Frequency Harmonics in a Single-Phase PV-Microinverter System

Single-phase microinverters used in household applications draw pulsating power from its input dc source while delivering ac power output to loads. While this introduces double line frequency harmonics into the dc bus of the microinverters, which lead to poor operational efficiencies of input energy sources (like solar arrays and fuel-cells etc.), it also deteriorates the quality of power fed to ac loads. Traditionally, large electrolytic capacitors or auxiliary decoupling circuits are used to mitigate the above-mentioned problems, making the converter system heavy, bulky, and thus increases the cost. In this letter, a new approach based on a simple pulsewidth modulation is proposed for single-phase microinverter system, aimed at mitigating the ill effects of double line frequency harmonics on both the dc side and ac side of the inverter. It is shown that by allowing a voltage swing of about 20% on the dc bus can significantly bring down the capacitance requirement by a factor of 3 to 5. Thus enabling, smaller and more durable film capacitors to be deployed instead of the bulky electrolytic capacitors. The envisaged approach is simulated and experimentally validated to support the claims on a laboratory setup.
Pediatric Trauma: Current Concepts and Treatments

Injured children represent a complex management problem for the trauma surgeon. Physiologic and psychological factors have been shown to influence outcome; however, more importantly, injury patterns and treatment algorithms differ from those recommended for adults. Children often do well after major injuries, but surgeons must use appropriate treatment to maximize the physiologic responses and the innate healing abilities of the growing child. Historically, surgeons have defined childhood as prepubertal, but a child's physiologic response to injury extends well into the third decade of life, making treatment of a 20-year-old similar to that of a 10-year-old, rather than that of a 40-year-old. The distribution of pediatric trauma facilities across the country has limited the access of the injured child to these centers. Adult centers more often serve as the first and definitive treatment provider for children. This article reviews the current concepts of trauma treatments for children. It is hoped that the adult trauma surgeons caring for injured children might gain information that will be of assistance in their daily practice.
Prestack and poststack inversion using a physics-guided convolutional neural network

An inversion algorithm is commonly used to estimate the elastic properties, such as P-wave velocity ([Formula: see text]), S-wave velocity ([Formula: see text]), and density ([Formula: see text]) of the earth’s subsurface. Generally, the seismic inversion problem is solved using one of the traditional optimization algorithms. These algorithms start with a given model and update the model at each iteration, following a physics-based rule. The algorithm is applied at each common depth point (CDP) independently to estimate the elastic parameters. Here, we have developed a technique using the convolutional neural network (CNN) to solve the same problem. We perform two critical steps to take advantage of the generalization capability of CNN and the physics to generate synthetic data for a meaningful representation of the subsurface. First, rather than using CNN as in a classification type of problem, which is the standard approach, we modified the CNN to solve a regression problem to estimate the elastic properties. Second, again unlike the conventional CNN, which is trained by supervised learning with predetermined label (elastic parameter) values, we use the physics of our forward problem to train the weights. There are two parts of the network: The first is the convolution network, which takes the input as seismic data to predict the elastic parameters, which is the desired intermediate result. In the second part of the network, we use wave-propagation physics and we use the output of the CNN to generate the predicted seismic data for comparison with the actual data and calculation of the error. This error between the true and predicted seismograms is then used to calculate gradients, and update the weights in the CNN. After the network is trained, only the first part of the network can be used to estimate elastic properties at remaining CDPs directly. We determine the application of physics-guided CNN on prestack and poststack inversion problems. To explain how the algorithm works, we examine it using a conventional CNN workflow without any physics guidance. We first implement the algorithm on a synthetic data set for prestack and poststack data and then apply it to a real data set from the Cana field. In all the training examples, we use a maximum of 20% of data. Our approach offers a distinct advantage over a conventional machine-learning approach in that we circumvent the need for labeled data sets for training.
SIMULATION-AIDED VALUE STREAM MAPPING FOR PRODUCTIVITY PROGRESSION IN A STEEL SHAFT MANUFACTURING ENVIRONMENT

Productivity improvement in the steel industry is pivotal to achieving competiveness that stimulate the economic growth of a country. In the past decade, the steel shaft manufacturing industry has experienced low productivity rates, making it difficult to compete at a global level. In light of this, the aim of this research study is to investigate the various process wastes and bottlenecks that limit the productivity progression of a steel shaft manufacturing environment, using integrated value stream mapping and system simulation methodologies. Data captured through the system observation of the shaft manufacturing process of a steel company was used to map and simulate the system. The results of the current state mapping of the steel shaft manufacturing environment revealed the various process wastes present in this system. The result of the simulation of the system revealed that the system bottlenecks were the saw master and milling stations. The strategic interventions in the saw master and milling stations improved these stations throughput from 959 to 1 218 (27%) and 624 to 1 003 (60.74%) components respectively. The work-in-progress components generated in the entire system after the strategic interventions reduced from 415 to 17.
Influence of Soil pH on s-Triazine Availability to Plants

Field studies indicated that liming an acid Bladen silt loam from pH 5.5 to 7.5 increased the phytotoxicity of atrazine [2-chloro-4-(ethylamino)-6-(isopropylamino)-s-triazine] and prometryn [2,4-bis-(isopropylamino)-6-methyoxy-s-triazine]. Liming greatly increased the persistence of atrazine, but did not affect prometryn dissipation. Liming increased the 14C-concentration present in the shoots of corn (Zea Mays L. ‘Pioneer 3369A’), cotton (Gossypium hirsutum L. ‘Coker 201’), and soybeans [Glycine Max (L.) Merr. ‘Ransom’] from soil treated with 14C-ring labeled atrazine, prometryn, and hydroxyatrazine [2-hydroxy-4-(ethylamino)-6-(isopropylamino)-s-triazine] in greenhouse studies. Decreases in 14C-uptake by the crops were associated with adsorption and degradation of the compounds in the soil. Atrazine was taken up in much greater amounts than hydroxyatrazine. Cotton absorbed less of the s-triazines than soybeans or corn from soil.
Service orientation–based tool for assessing and improving service design and development practices in manufacturing industry

Industrial manufacturing companies are increasingly shifting their focus from products to services, challenging their development functions at the operational and strategic levels. When strengthening a company’s service orientation, attention must be paid to service experience and value co-creation, which create momentum for service design. However, the research has thus far been silent on concrete guidelines for how to proceed with servitisation. In this article, we propose a service orientation–based tool to facilitate service development and design in industrial manufacturing companies. The tool combines previous research on NSD and service design with empirical investigations and the authors’ experience. The tool provides a framework for assessing and improving the organisation and implementation of service design and development in industrial manufacturing companies.
A Machine Learning-Based Algorithm for Joint Scheduling and Power Control in Wireless Networks

Wireless network resource allocation is an important issue for designing Internet of Things systems. In this paper, we consider the problem of wireless network capacity optimization that involves issues such as flow allocation, link scheduling, and power control. We show that it can be decomposed into a linear program and a nonlinear weighted sum-rate maximization problem for power allocation. Unlike most traditional methods that iteratively search the optimal solutions of the nonlinear subproblem, we propose to directly compute approximated solutions based on machine learning techniques. Specifically, the learning systems consist of both support vector machines (SVMs) and deep belief networks (DBNs) that are trained based on offline computed optimal solutions. In the running phase, the SVMs perform classification for each link to decide whether to use maximal transmit power or be turned off. At the same time, the DBNs compute an approximation of the optimal power allocation. The two results are combined to obtain an approximated solution of the nonlinear program. Simulation results demonstrate the effectiveness of the proposed machine learning-based algorithm.
Size-independent vs. size-dependent policies in scheduling heavy-tailed distributions

We study the problem of scheduling jobs on a two-machine distributed server, where the job size distribution is heavy-tailed. We focus on two distributions, for which we prove that the performance of the optimal size-independent policy is asymptotically worse than that of a simple size-dependent policy. First, we consider a simple distribution where incoming jobs can only be of two possible sizes. The motivation is that with two largely different sizes, the simple distribution captures the important aspects of a heavy tail. Second, we extend to a bounded Pareto distribution, which has an actual heavy tail. For both cases, we analyze the performance with regards to slowdown (waiting time divided by job size) for several size-independent and size-dependent policies. We see that the size-dependent policies perform better, and then go on to prove that even the best size-independent policy cannot achieve the same performance. We conclude that as we increase the variance of our job size distribution, the gap between size-independent and size-dependent policies grows. Thesis Supervisor: John N. Tsitsiklis Title: Clarence J Lebel Professor of Electrical Engineering, MIT Thesis Supervisor: Sudhendu Rai Title: Principal Scientist, Xerox Corporation
Improving Research Participant Ethics

The undergraduate psychology curriculum often does not address guidelines for acceptable participant behavior. This two-part study tested the efficacy of a recently developed online learning module on ethical perceptions, knowledge, and behavior. In the preliminary quasi-experiment, students who viewed the module did not have higher end-of-semester ethical perceptions than a control group, although the experimental group demonstrated increased ethical knowledge and behavior than the control group. Study 2 replicated these findings with a pretest–posttest experimental design at another university. These findings lend support for the module increasing ethical knowledge and behavior, although not necessarily perceptions. However, exploratory analyses suggested that ethical perceptions appear to increase across all research participants through experience.
Failure protection in layered networks with shared risk link groups

The shared risk link group (SRLG) has been widely recognized as a fundamental concept in layered network design by the industry. However, several issues related to SRLG protections that are of both theoretical interest and practical importance have not been explored fully. Two major issues are avoiding failures caused by "traps" in finding backup paths, and minimizing the total network capacity requested by active and backup paths. In this article, we highlight the significance of the trap problem in layered networks with SRLG and evaluate the performance of several existing SRLG protection schemes in terms of trap avoidance and bandwidth efficiency, as well as their complexities. We also demonstrate that a simple yet intelligent heuristic algorithm can achieve good performance.