Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluating classification performance of biomarkers in two‐phase case‐control studies

Biomarkers are playing an increasingly important role in disease screening, early detection, and risk prediction. The two‐phase case‐control sampling study design is widely used for the evaluation of candidate biomarkers. The sampling probabilities for cases and controls in the second phase can often depend on other covariates (sampling strata). This biased sampling can lead to invalid inference on a biomarker's classification accuracy if not properly accounted for. In this paper, we adopt the idea of inverse probability weighting and develop inverse probability weighting–based estimators for various measures of a biomarker's classification performance, including the points on the receiver operating characteristics (ROCs) curve, the area under the ROC curve (area under the curve), and the partial area under the curve. In particular, we consider classification accuracy estimators using sampling weights estimated conditionally on sampling strata and further improve their efficiency through the use of estimated weights that additionally take into account the auxiliary variables available from the phase‐one cohort. We develop asymptotic properties of the proposed estimators and provide analytical variance for making inference. Extensive simulation studies demonstrate excellent performance of the proposed weighted estimators, while the traditional empirical estimator can be severely biased. We also investigate the advantages in efficiency gain for estimating various classification accuracy estimators through the use of auxiliary variables in addition to sampling strata and apply the proposed method to examples from a renal artery stenosis study and a prostate cancer study.
Multimorbidity, frailty and chronic obstructive pulmonary disease

The overwhelming majority of people with chronic obstructive pulmonary disease (COPD) have at least one coexisting medical condition often conceptualized as ‘comorbidities’. These coexisting conditions vary in severity and impact; it is likely that for some patients, COPD is not their most important or severe condition. The concepts of multimorbidity and frailty may be useful to understand the broader needs of people with COPD undergoing pulmonary rehabilitation. Multimorbidity describes the coexistence of two or more chronic conditions, without reference to a primary condition. Best care for people with multimorbidity has been described as a shift from providing disease-focused to patient-centred care. Pulmonary rehabilitation is well placed to deliver such care as it focuses on optimizing function, encourages integration across care settings, values input from multidisciplinary teams and measures patient-important outcomes. When designing optimal pulmonary rehabilitation services for people with multimorbidity, the concept of frailty may be useful. Frailty focuses on impairments rather than medical conditions including impairments in mobility, strength, balance, cognition, nutrition, endurance, mood and physical activity. Emerging data suggest that frailty may be modifiable with pulmonary rehabilitation. The challenge for pulmonary rehabilitation clinicians is to broaden our perspective on the role and outcomes of pulmonary rehabilitation for people with multimorbidity.
The effect of age and hearing loss on partner-directed gaze in a communicative task

The study examined the partner-directed gaze patterns of old and young talkers in a task (DiapixUK) that involved two people (a lead talker and a follower) engaging in a spontaneous dialogue. The aim was (1) to determine whether older adults engage less in partner-directed gaze than younger adults by measuring mean gaze frequency and mean total gaze duration; and (2) examine the effect that mild hearing loss may have on older adult’s partner-directed gaze. These were tested in various communication conditions: a no barrier condition; BAB2 condition in which the lead talker and the follower spoke and heard each other in multitalker babble noise; and two barrier conditions in which the lead talker could hear clearly their follower but the follower could not hear the lead talker very clearly (i.e., the lead talker’s voice was degraded by babble (BAB1) or by a Hearing Loss simulation (HLS). 57 single-sex pairs (19 older adults with mild Hearing Loss, 17 older adults with Normal Hearing and 21 younger adults) participated in the study. We found that older adults with normal hearing produced fewer partner-directed gazes (and gazed less overall) than either the older adults with hearing loss or younger adults for the BAB1 and HLS conditions. We propose that this may be due to a decline in older adult’s attention to cues signaling how well a conversation is progressing. Older adults with hearing loss, however, may attend more to visual cues because they give greater weighting to these for understanding speech.
A Simple and Rapid Method for Deposition and Measurement of Drug Transport Across Air Interface Respiratory Epithelia

The purpose of this study was to present a novel and simple drug deposition method to evaluate drug transport of aerosol microparticles across airway epithelial cells. Microparticles containing ciprofloxacin HCl (Cip) and doxycycline (Dox), alone or in a 50:50% w/w ratio, were spray dried and suspended using 2H, 3H-perfluoropentane, model propellant. The suspension was then used to assess deposition, and transport of these drug microparticles across sub-bronchial epithelial Calu-3 cells was also studied. In comparison with other methods of depositing microparticles, this proposed method, using drug suspended in HPFP, provides control over the amount of drugs applied on the surface of the cells. Therefore, cell permeability studies could be conducted with considerably smaller and more reproducible doses, without the physicochemical characteristics of the drugs being compromised or the use of modified pharmacopeia impactors. The suspension of microparticles in HPFP as presented in this study has provided a non-toxic, simple, and reproducible novel method to deliver and study the permeability of specific quantity of drugs across respiratory epithelial cells in vitro.
Useful ToPIC: Self-Tuning Strategies to Enhance Latent Dirichlet Allocation

TToPIC (Tuning of Parameters for Inference of Concepts) is a distributed self-tuning engine whose aim is to cluster collections of textual data into correlated groups of documents through a topic modeling methodology (i.e., LDA). ToPIC includes automatic strategies to relieve the end-user of the burden of selecting proper values for the overall analytics process. ToPIC's current implementation runs on Apache Spark, a state-of-the-art distributed computing framework. As a case study, ToPIC has been validated on three real collections of textual documents characterized by different distributions. The experimental results show the effectiveness and efficiency of the proposed solution in analyzing collections of documents without tuning algorithm parameters and in discovering cohesive and well-separated groups of documents with a similar topic.
An Energy Efficient and QoS Aware Routing Algorithm Based on Data Classification for Industrial Wireless Sensor Networks

In industrial wireless sensor networks, an energy-efficient quality-of-service (QoS) routing algorithm is very important to ensure that the key sensing data can be forwarded in a reliable path and solve the energy balance problem. In this paper, we classify the industrial sensing data into three data types and set their priority. Furthermore, we give the reliability parameters and timeliness parameters, and we propose and establish the candidate forwarding node set in order to balance the energy consumption. Subsequently, an energy-efficient and QoS aware routing algorithm is designed, and in this routing algorithm, different kinds of data can be forwarded with different strategies. Furthermore, the most important industrial sensing data are guaranteed to be transmitted to the sink node reliably and timely and common data can be transmitted effectively, too. All these data will be forwarded to the optimal relay node under the circumstance of that the data requirements of real time and reliability are satisfied. The simulation results show that the high timeliness event data can be transmitted real time and reliability than the other type of data. And our proposed routing algorithm is effective compared with the similar algorithms.
How Taxonomic and Thematic Associations in Semantic Memory Modulate Recall in Young Through Old-Old Adults

The aim of the current study was to investigate how the taxonomic and thematic organization of semantic long-term memory affected the recall performance of adults and older participants on a complex semantic working memory (SWM) task. Taxonomic and thematic classification are the two main systems used to organize knowledge: taxonomic information is hierarchically structured and typically independent of space and time, whereas thematically grouped concepts are horizontal and strictly context-dependent. Generally, thematic connections (more intuitive and experience-based) are formed earlier in development, while taxonomic links (more abstract and logic-based) are acquired later. We set out to explore whether this developmental pattern reverses with age, hypothesizing that the more complex form of memory organization (i.e., taxonomic) would play a lesser role in facilitating recall in the old, whereas thematic organization would be better preserved. Participants (aged 18 to 85 years) were asked to recall 60 words in sets of increasing span; the words were featured in lists organized to force a taxonomic association, a thematic association, or no semantic association. The results clearly showed that task accuracy varied more across age groups for taxonomically linked items than for thematically linked ones.
Relationships among perceived quality of healthcare services, satisfaction and behavioural intentions of international students in Kuala Lumpur, Malaysia: a cross-sectional study

Objective The current study aimed to investigate the relationships among the perceived quality of healthcare services, satisfaction and behavioural intentions among international students in Kuala Lumpur, Malaysia. Setting A cross-sectional study on public universities in Kuala Lumpur, Malaysia. Participants All participants in this study were international students joining public universities in Kuala Lumpur, Malaysia. Primary independent variable Perceived quality of healthcare services measured on a SERVQUAL scale. Primary dependent variable Participants’ satisfaction of healthcare services assessed using five items. Secondary dependent variable Behavioural intentions measured on six items. Results Of the 556 international students, 500 (90%) completed the survey. The study used structural equation modelling (SEM) through the AMOS (Analysis of Moment Structures) software to analyse the data. SEM analyses showed that the perceived quality of healthcare services significantly and directly affected satisfaction, with a value of 89% and an effect size of 0.78. It also had a significant indirect impact on the behavioural intentions (0.78) of international students. The results indicated that participants’ satisfaction had a statistically significant impact on their behavioural intentions (0.77). Conclusion Perceived quality of care is an important driver of international students’ satisfaction and their behavioural intention with healthcare services. Such relations of effects among the three investigated factors were also positive and significant.
A Rank Scheduling Mechanism for Fog Environments

With the advent of the Internet of Things many applications emerged that are not suitable for well-known paradigms like the Cloud, requiring its extension to provide more features to final users. Thus, the Fog rises as an extension to the Cloud able to provide mobility support, geographical distribution, and lower latency, by moving the services closer to the users, to the edge of the network. This new environment located at the edge comes with its own orchestration challenges. Among the orchestration functions that must be adapted to this new environment is scheduling. This paper presents a simple scheduling algorithm for Fog federative environments that organizes Fog instances into divisions for task assignment. Experimental results show that this approach could be particularly beneficial for critical time applications, commonly located at the Fog.
Changes in expression of the autophagy-related genes microtubule-associated protein 1 light chain 3β and autophagy related 7 in skeletal muscle of fattening Japanese Black cattle: a pilot study

Objective Autophagy is a bulk degradation system for intracellular proteins which contributes to skeletal muscle homeostasis, according to previous studies in humans and rodents. However, there is a lack of information on the physiological role of autophagy in the skeletal muscle of meat animals. This study was planned as a pilot study to investigate changes in expression of two major autophagy-related genes, microtubule-associated protein 1 light chain 3β (MAP1LC3B) and autophagy related 7 (ATG7) in fattening beef cattle, and to compare them with skeletal muscle growth. Methods Six castrated Japanese Black cattle (initial body weight: 503±20 kg) were enrolled in this study and fattened for 7 months. Three skeletal muscles, M. longissimus, M. gluteus medius, and M. semimembranosus, were collected by needle biopsy three times during the observation period, and mRNA levels of MAP1LC3B and ATG7 were determined by quantitative reverse-transcription polymerase chain reaction. The expression levels of genes associated with the ubiquitin-proteasome system, another proteolytic mechanism, were also analyzed for comparison with autophagy-related genes. In addition, ultrasonic scanning was repeatedly performed to measure M. longissimus area as an index of muscle growth. Results Our results showed that both MAP1LC3B and ATG7 expression increased over the observation period in all three skeletal muscles. Interestingly, the increase in expression of these two genes in M. longissimus was highly correlated with ultrasonic M. longissimus area and body weight. On the other hand, the expression of genes associated with the ubiquitin-proteasome system was unchanged during the same period. Conclusion These findings suggest that autophagy plays an important role in the growth of skeletal muscle of fattening beef cattle and imply that autophagic activity affects meat productivity.
Suture Breakage Warning System for Robotic Surgery

As robotic surgery has increased in popularity, the lack of haptic feedback has become a growing issue due to the application of excessive forces that may lead to clinical problems such as intraoperative and postoperative suture breakage. Previous suture breakage warning systems have largely depended on visual and/or auditory feedback modalities, which have been shown to increase cognitive load and reduce operator performance. This work catalogues a new sensing technology and haptic feedback system (HFS) that can reduce instances of suture failure without negatively impacting performance outcomes including knot quality. Suture breakage is common in knot-tying as the pulling motion introduces prominent shear forces. A shear sensor mountable on the da Vinci robotic surgical system's Cadiere grasper detects forces that correlate to the suture's internal tension. HFS then provides vibration feedback to the operator as forces near a particular material's failure load. To validate the system, subjects tightened a total of four knots, two with the Haptic Feedback System (HFS) and two without feedback. The number of suture breakages were recorded and knot fidelity was evaluated by measuring knot slippage. Results showed that instances of suture failure were significantly reduced when HFS was enabled (p = 0.0078). Notably, knots tied with HFS also showed improved quality compared to those tied without feedback (p = 0.010). The results highlight the value of HFS in improving robotic procedure outcomes by reducing instances of suture failures, producing better knots, and reducing the need for corrective measures.
Time Series Analysis of Clickstream Logs from Online Courses

Due to the rapidly rising popularity of Massive Open Online Courses (MOOCs), there is a growing demand for scalable automated support technologies for student learning. Transferring traditional educational resources to online contexts has become an increasingly relevant problem in recent years. For learning science theories to be applicable, educators need a way to identify learning behaviors of students which contribute to learning outcomes, and use them to design and provide personalized intervention support to the students. Click logs are an important source of information about students' learning behaviors, however current literature has limited understanding of how these behaviors are represented within click logs. In this project, we have exploited the temporal dynamics of student behaviors both to do behavior modeling via graphical modeling approaches and to do performance prediction via recurrent neural network approaches in order to first identify student behaviors and then use them to predict their final outcome in the course. Our experiments showed that the long short-term memory (LSTM) model is capable of learning long-term dependencies in a sequence and outperforms other strong baselines in the prediction task. Further, these sequential approaches to click log analysis can be successfully imported to other courses when used with results obtained from graphical model behavior modeling.
Adaptive system of mutual positioning for controlling the groups of unmanned aerial vehicles

In this paper we consider the method of mutual positioning in the control system of groups of unmanned aerial vehicles (UAVs). For this purpose the exchange of coordinates is provided in the system. Each UAV has a Global Navigation Satellite System (GNSS) receiver and its own radar station with the active response. The integrated cyclogram of time in the presence of external synchronization by signals of GNSS is implemented at all interacting stations. The information exchange is organized as a fully connected system with time-division multiplexing. The structure of the transmitted data is determined. We offer a cluster system due to the rapidly increasing amount of signals in the fully connected system. It means that a group of UAVs is divided into subgroups. Each subgroup has a leader. The information exchange between leaders of subgroups is also provided. We consider the method of coordinates estimation based on the integration of measurement results obtained by using GNSS and the measurements from radars of UAVs. Mutual coordinate determination in the system has several stages: reception of the information from GNSS and airborne radars; secondary processing of GNSS data and the airborne radar information by means of Kalman filters; getting the resulting estimate by the integration of results after secondary information processing. It is researched how the choice of initial conditions and parameters of filters influences the quality of resulting estimation. The influence of update time in measuring systems with the active response on the accuracy of estimation by using Kalman filter is examined. The research is conducted by mathematical model method. The comparative analysis of two algorithms of integration is done. The relationship between computational cost of the algorithm of integration and accuracy of the resulting estimation is determined. The influence of quality of initial estimations on the accuracy of the Kalman filter resulting estimation is analyzed. At the same time weight coefficients are determined on the basis of the estimation accuracy of coordinate and ranging information filters. It is shown that information loss caused by fading influences the resulting errors of measurements. For these conditions we also consider the case of the movement of UAVs with big acceleration. It is concluded that the structure and parameters of the system should be adapted to the changing group members and conditions of obtaining coordinate information.
Cellular Sources and Regional Variations in the Expression of the Neuroinflammatory Marker Translocator Protein (TSPO) in the Normal Brain

The inducible expression of the mitochondrial translocator protein 18 kDa (TSPO) by activated microglia is a prominent, regular feature of acute and chronic-progressive brain pathology. This expression is also the rationale for the continual development of new TSPO binding molecules for the diagnosis of “neuroinflammation” by molecular imaging. However, there is in the normal brain an ill-defined, low-level constitutive expression of TSPO. Taking advantage of healthy TSPO knockout mouse brain tissue to validate TSPO antibody specificity, this study uses immunohistochemistry to determine the regional distribution and cellular sources of TSPO in the normal mouse brain. Fluorescence microscopy revealed punctate TSPO immunostaining in vascular endothelial cells throughout the brain. In the olfactory nerve layers and glomeruli of the olfactory bulb, choroid plexus and ependymal layers, we confirm constitutive TSPO expression levels similar to peripheral organs, while some low TSPO expression is present in regions of known neurogenesis, as well as cerebellar Purkinje cells. The distributed-sparse expression of TSPO in endothelial mitochondria throughout the normal brain can be expected to give rise to a low baseline signal in TSPO molecular imaging studies. Finally, our study emphasises the need for valid and methodologically robust verification of the selectivity of TSPO ligands through the use of TSPO knockout tissues.
Reuse Considerations in Evolving Software Products: The Software Product Line Perspective

The evolution of software products is obtained by continuously expanding the variety of features, qualities, and functions of existing products. When similar software products are developed, two important reuse decisions are: (1) whether to develop a software product or adapt organizational software assets, commonly termed core assets; and (2) whether to develop a core asset or extract it from existing product artifacts, e.g., using mining techniques. While many works study how to reuse effectively and efficiently, the considerations taken when reaching such decisions are somehow overlooked or taken as intuitive or self-understood. To this end, we present the results of an exploratory study that investigates the engineering, organizational, and business considerations taking a software product line perspective.