Miracle-dz/UniFAR-FTUs huggingface dataset:
Iranian Nursing Student–patient Health Communication in Medical Surgical Wards

Background: Health communication (HC) is considered an important task of nurses to provide high quality and holistic care as well as to improve patient health. The nursing student–patient HC is an abstract concept and needs to be clarified. Therefore, this study was conducted to increase the knowledge about nursing students' HC with patients by considering various participants' viewpoints. Materials and Methods: In this conventional qualitative content analysis, 18 semi-structured interviews were conducted with six nursing students, six nursing instructors, and six patients in educational hospitals affiliated to the University of Medical Sciences. Credibility, confirmability, dependability, and transferability were established to validate the trustworthiness of the data. The process of data collection and analysis lasted 9 months. Results: After data analysis, two categories were generated: (A) “junior nursing student–patient communication,” with two subcategories of “performing social communication with patients” and “failure to build therapeutic relationships with patients,” and (B) “senior nursing student–patient communication” with two subcategories of “establishing effective communication with patients” and “performing one-way communication with patients. ” Conclusions: More attention should be paid to improve HC through shifting towards student-centered approaches in nursing curriculum. Further, role model nurses and clinical educators should guide nursing students for institutionalizing HC in future nurses.
A New Design of a Single-Device 3D Hall Sensor: Cross-Shaped 3D Hall Sensor

In this paper, a new single-device three-dimensional (3D) Hall sensor called a cross-shaped 3D Hall device is designed based on the five-contact vertical Hall device. Some of the device parameters are based on 0.18 μm BCDliteTM technology provided by GLOBALFOUNDRIES. Two-dimensional (2D) and 3D finite element models implemented in COMSOL are applied to understand the device behavior under a constant magnetic field. Besides this, the influence of the sensing contacts, active region’s depth, and P-type layers are taken into account by analyzing the distribution of the voltage along the top edge and the current density inside the devices. Due to the short-circuiting effect, the sensing contacts lead to degradation in sensitivities. The P-type layers and a deeper active region in turn are responsible for the improvement of sensitivities. To distinguish the P-type layer from the active region which plays the dominant role in reducing the short-circuiting effect, the current-related sensitivity of the top edge (Stop) is defined. It is found that the short-circuiting effect fades as the depth of the active region grows. Despite the P-type layers, the behavior changes a little. When the depth of the active region is 7 μm and the thickness of the P-type layers is 3 μm, the sensitivities in the x, y, and z directions can reach 91.70 V/AT, 92.36 V/AT, and 87.10 V/AT, respectively.
SSSL: Shoulder Surfing Safe Login

Classical PIN-entry methods are vulnerable to a broad class of observation attacks (shoulder surfing, key-logging). A number of alternative PIN-entry methods that are based on human cognitive skills have been proposed. These methods can be classified into two classes regarding information available to a passive adversary: (i) the adversary fully observes the entire input and output of a PIN-entry procedure, and (ii) the adversary can only partially observe the input and/or output. In this paper we propose a novel PIN-entry scheme - Shoulder Surfing Safe Login (SSSL). SSSL is a challenge response protocol that allows a user to login securely in the presence of the adversary who can observe (via key-loggers, cameras) user input. This is accomplished by restricting the access to SSSL challenge values. Compared to existing solutions, SSSL is both user-friendly (not mentally demanding) and cost efficient. Our usability study reveals that the average login time with SSSL is around 8 sec in a 5-digit PIN scenario. We also show the importance of considering side-channel timing attacks in the context of authentication schemes based on human cognitive skills.
Kinetics of the CaO/Ca(OH)2 Hydration/Dehydration Reaction for Thermochemical Energy Storage Applications

The calcium oxide hydration/dehydration reaction is proposed as a suitable reaction couple for thermochemical energy storage systems. However, limited work has been reported on the reaction kinetics of CaO/Ca(OH)2 under appropriate operation conditions for storage applications involving fluidized beds. This study focuses on the effect of temperature, partial steam pressure, and particle size upon the intrinsic hydration and dehydration reaction kinetics when natural materials are used. The experimental data have been fitted satisfactorily to a shrinking core model for both hydration and dehydration reactions, at reaction temperatures between 400 and 560 °C and partial steam pressures between 0 and 100 kPa. The reaction rates measured are higher than those previously reported in the literature. In the case of large particle sizes of natural material, particle attrition has been detected indicating the need to develop more suitable materials for thermochemical energy storage applications.
Human Object Identification for Human-Robot Interaction by Using Fast R-CNN

This paper proposes a human object identification by using a simplified fast region-based convolutional network (R-CNN). Human identification is a problem of considerable practical interest. Here, we propose the state-of-the art method which is tested for major pedestrian datasets. Human detection consists of the body part detectors which detect head and shoulder, torso, and pair of legs, with three, two and four different appearances respectively. These detectors are integrated as to identify the human object with different poses. Fast R-CNN is a well-known method for object recognition using deep CNN. Hybrid body part detector demonstrates the merits for partially occluded human detection by integrating the scores of the individual part detectors based on the occlusion map. The highest merging score is the best configuration to evaluate the detection score of the human detector. Experiments on two public datasets (INRIA and Caltech) show the effectiveness of the proposed approach.
Citywide Estimation of Traffic Dynamics via Sparse GPS Traces

Traffic congestion is a perpetual challenge in metropolitan areas around the world. The ability to understand traffic dynamics is thus critical to effective traffic control and management. However, estimation of traffic conditions over a large-scale road network has proven to be a challenging task for two reasons: first, traffic conditions are intrinsically stochastic; second, the availability and quality of traffic data vary to a great extent. Traditional traffic monitoring systems that exist mostly on major roads and highways are insufficient to recover the traffic conditions for an entire network. Recent advances in GPS technology and the resulting rich data sets offer new opportunities to improve upon such traditional means, by providing much broader coverage of road networks. Despite that, such data are limited by their spatial-temporal sparsity in practice. To address these issues, we have developed a novel framework to estimate travel times, traversed paths, and missing values over a large-scale road network using sparse GPS traces. Our method consists of two phases. In the first phase, we adopt the shortest travel time criterion based on Wardrop's Principles in the map-matching process. With an improved traveltime allocation technique, we have achieved up to 52.5% relative error reduction in network travel times compared to a state-of-the-art method [1]. In the second phase, we estimate missing values using Compressed Sensing algorithm, thereby reducing the number of required measurements by 94.64%.
Choosing an Animal Model for the Study of Functional Dyspepsia

Functional dyspepsia (FD) is a common functional gastrointestinal disorder with pain or discomfort in the upper abdomen as the main characteristic. The prevalence of FD worldwide varies between 5% and 11%. This condition adversely affects attendance and productivity in the workplace. Emerging evidence is beginning to unravel the pathophysiologies of FD, and new data on treatment are helping to guide evidence-based practice. In order to better understand the pathophysiologies of FD and explore better treatment options, various kinds of animal models of FD have been developed. However, it is unclear which of these models most closely mimic the human disease. This review provides a comprehensive overview of the currently available animal models of FD in relationship to the clinical features of the disease. The rationales, methods, merits, and disadvantages for modelling specific symptoms of FD are discussed in detail.
Joint care can outweigh costs of nonkin competition in communal breeders

&NA; Competition between offspring can greatly influence offspring fitness and parental investment decisions, especially in communal breeders where unrelated competitors have less incentive to concede resources. Given the potential for escalated conflict, it remains unclear what mechanisms facilitate the evolution of communal breeding among unrelated females. Resolving this question requires simultaneous consideration of offspring in noncommunal and communal nurseries, but such comparisons are missing. In the Seychelles warbler Acrocephalus sechellensis, we compare nestling pairs from communal nests (2 mothers) and noncommunal nests (1 mother) with singleton nestlings. Our results indicate that increased provisioning rate can act as a mechanism to mitigate the costs of offspring rivalry among nonkin. Increased provisioning in communal broods, as a consequence of having 2 female parents, mitigates any elevated costs of offspring rivalry among nonkin: per‐capita provisioning and survival was equal in communal broods and singletons, but lower in noncommunal broods. Individual offspring costs were also more divergent in noncommunal broods, likely because resource limitation exacerbates differences in competitive ability between nestlings. It is typically assumed that offspring rivalry among nonkin will be more costly because offspring are not driven by kin selection to concede resources to their competitors. Our findings are correlational and require further corroboration, but may help explain the evolutionary maintenance of communal breeding by providing a mechanism by which communal breeders can avoid these costs.
Review of Research on Template Methods in Preparation of Nanomaterials

The nanomaterials have been widely used in various fields, such as photonics, catalysis, and adsorption, because of their unique physical and chemical properties. Therefore, their production methods are of utmost importance. Compared with traditional synthetic methods, the template method can effectively control the morphology, particle size, and structure during the preparation of nanomaterials, which is an effective method for their synthesis. The key for the template method is to choose different templates, which are divided into hard template and soft template according to their different structures. In this paper, the effects of different types of templates on the morphology of nanomaterials during their preparation are investigated from two aspects: hard template and soft template, combined with the mechanism of action.
Administration of mesenchymal stem cells during ECMO results in a rapid decline in oxygenator performance

Mesenchymal stem cells (MSCs) have attracted attention as a potential therapy for Acute Respiratory Distress Syndrome (ARDS). At the same time, the use of extracorporeal membrane oxygenation (ECMO) has increased among patients with severe ARDS. To date, early clinical trials of MSCs in ARDS have excluded patients supported by ECMO. Here we provide evidence from an ex-vivo model of ECMO to suggest that the intravascular administration of MSCs during ECMO may adversely impact the function of a membrane oxygenator. The addition of clinical grade MSCs resulted in a reduction of flow through the circuit in comparison to controls (0.6 ±0.35 L min-1vs 4.12 ± 0.03 L min-1, at 240 minutes) and an increase in the transoygenator pressure gradient (101±9 mmHg vs 21±4 mmHg, at 240 minutes). Subsequent immunohistochemistry analysis demonstrated quantities of MSCs highly adherent to membrane oxygenator fibres. This study highlights the potential harm associated with MSC therapy during ECMO and suggests further areas of research required to advance the translation of cell therapy in this population.
A FrameNet-based Approach for Annotating Natural Language Descriptions of Software Requirements

As most software requirements are written in natural language, they are unstructured and do not adhere to any formalism. Processing them automatically—within the context of software requirements engineering tasks—thus becomes difficult for machines. As a step towards adding structure to requirements documents, we exploited frames in FrameNet and applied them to the semantic annotation of software descriptions. This was carried out through an approach based on automated lexical unit matching, manual validation and harmonisation. As a result, we produced a novel corpus of requirements documents containing software descriptions which have been assigned a total of 242 unique semantic frames overall. Our evaluation of the resulting annotations shows substantial agreement between our two annotators, encouraging us to pursue finer-grained semantic annotation as part of future work.
Improving Hydrolysis Characteristics of Xylanases by Site-Directed Mutagenesis in Binding-Site Subsites from Streptomyces L10608

The preparation of oligosaccharides via xylan hydrolysis is an effective way to add value to hemicellulosic material of agricultural waste. The bacterial strain Streptomyces L10608, isolated from soil, contains genes encoding xylanases of glucoside hydrolase family 10/11 (GH10/11), and these have been cloned to catalyze the production of xylooligosaccharide (XOS). To improve the XOS proportion of hydrolysates produced by xylanase, four amino acid residues were substituted by site-directed mutagenesis, and the mutant genes were overexpressed in Escherichia coli. Mutations replaced the codons encoding Asn214 (+2) and Asn86 (−2) by Ala and removed the Ricin B-lectin domain in GH10-xyn, and mutants Y115A (−2) and Y123A (−2) were produced for GH11-xyn. Interestingly, GH10-N86Q had significantly increased hydrolysis of XOS and almost eliminated xylose (X1) to <2.5%, indicating that the −2 binding site of GH10-xyn of L10608 is required for binding with xylotriose (X3). The hydrolytic activity of GH10-N86Q was increased approximately 1.25-fold using beechwood xylan as a substrate and had high affinity for the substrate with a low Km of about 1.85 mg·mL−1. Otherwise, there were no significant differences in enzymatic properties between GH10-N86Q and GH10-xyn. These mutants offer great potential for modification of xylanase with desired XOS hydrolysis.
Nonenvelopment Role for the ESCRT-III Complex during Human Cytomegalovirus Infection

ABSTRACT Secondary envelopment of human cytomegalovirus (HCMV) occurs through a mechanism that is poorly understood. Many enveloped viruses utilize the endosomal sorting complexes required for transport (ESCRTs) for viral budding and envelopment. Although there are conflicting reports on the role of the ESCRT AAA ATPase protein VPS4 in HCMV infection, VPS4 may act in an envelopment role similar to its function during other viral infections. Because VPS4 is normally recruited by the ESCRT-III complex, we hypothesized that ESCRT-III subunits would also be required for HCMV infection. We investigated the role of ESCRT-III, the core ESCRT scission complex, during the late stages of infection. We show that inducible expression of dominant negative ESCRT-III subunits during infection blocks endogenous ESCRT function but does not inhibit virus production. We also show that HCMV forms enveloped intracellular and extracellular virions in the presence of dominant negative ESCRT-III subunits, suggesting that ESCRT-III is not involved in the envelopment of HCMV. We also found that as with ESCRT-III, inducible expression of a dominant negative form of VPS4A did not inhibit the envelopment of virions or reduce virus titers. Thus, HCMV does not require the ESCRTs for secondary envelopment. However, we found that ESCRT-III subunits are required for efficient virus spread. This suggests a role for ESCRT-III during the spread of HCMV that is independent of viral envelopment. IMPORTANCE Human cytomegalovirus (HCMV) is a prevalent opportunistic pathogen in the human population. For neonatal and immunocompromised patients, HCMV infection can cause severe and possibly life-threatening complications. It is important to define the mechanisms of the viral replication cycle in order to identify potential targets for new therapies. Secondary envelopment, or acquisition of the membrane envelope, of HCMV is a mechanism that needs further study. Using an inducible fibroblast system to carefully control for the toxicity associated with blocking ESCRT-III function, this study determines that the ESCRT proteins are not required for viral envelopment. However, the study does discover a nonenvelopment role for the ESCRT-III complex in the efficient spread of the virus. Thus, this study advances our understanding of an important process essential for the replication of HCMV.
Impacts of packet collisions on link throughput in CSMA wireless networks

It is known that packet collisions in wireless networks will deteriorate system performance, hence substantial efforts have been made to avoid collision in multi-user access designs. Also, there have been many studies on throughput analysis of CSMA wireless networks. However, for a typical CSMA network in which not all nodes can sense each other, it is still not well investigated how link throughputs are affected by collisions. We note that in practical 802.11-like networks, the time is divided into mini-timeslots and packet collisions are in fact unavoidable. Thus, it is desirable to move forward to explore how collisions in such a network will affect system performance. Based on the collision-free ideal CSMA network (ICN) model, this paper attempts to analyze link throughputs when taking the backoff collisions into account and examine the effect of collisions on link throughputs. Specifically, we propose an Extended Ideal CSMA Network (EICN) model to characterize the collision effects as well as the interactions and dependency among links in the network. Based on EICN, we could directly compute link throughputs and collision probabilities. Simulations show that the EICN model is of high accuracy. Under various network topologies and protocol parameter settings, the computation error of link throughputs using EICN is kept to 4% or below. Interestingly, we find that unlike expected, the effect of collisions on link throughputs in a modest CSMA wireless network is not significant, which enriches our understanding on practical CSMA wireless networks such as Wi-Fi.
False Alarm Reduction in Atrial Fibrillation Detection Using Deep Belief Networks

We propose and validate a novel method to reduce the false alarm (FA) rate caused by poor-quality electrocardiogram (ECG) signal measurement during atrial fibrillation (AFib) detection. A deep belief network is used to differentiate acceptable from unacceptable ECG segments. To validate the method, eight different levels of ECG quality are provided by artificially contaminating ECG records, from the MIT-BIH AFib database, with motion artifact from the MIT-BIH noise stress test database. ECG segments classified as “unacceptable,” in terms of signal quality, are restricted from AFib detection process. Results are evaluated for each level of quality and compared to AFib detection algorithm performance when ECGs of each level of quality are applied to it without performing any classification. Our results show that AFib detection performance for ECG with high signal-to-noise ratio (SNR) is minimally affected by this FA reduction approach. For clean ECG (no added noise), the AFib detection accuracy was 87%, without and with FA reduction. For ECG, with an SNR of −20 dB, the performance of AFib detection is markedly decreased with an accuracy of 58.7%; however, with FA reduction (using our method) the accuracy was increased to 81%.
Robust Feature-Based Automated Multi-View Human Action Recognition System

Automated human action recognition has the potential to play an important role in public security, for example, in relation to the multiview surveillance videos taken in public places, such as train stations or airports. This paper compares three practical, reliable, and generic systems for multiview video-based human action recognition, namely, the nearest neighbor classifier, Gaussian mixture model classifier, and the nearest mean classifier. To describe the different actions performed in different views, view-invariant features are proposed to address multiview action recognition. These features are obtained by extracting the holistic features from different temporal scales which are modeled as points of interest which represent the global spatial-temporal distribution. Experiments and cross-data testing are conducted on the KTH, WEIZMANN, and MuHAVi datasets. The system does not need to be retrained when scenarios are changed which means the trained database can be applied in a wide variety of environments, such as view angle or background changes. The experiment results show that the proposed approach outperforms the existing methods on the KTH and WEIZMANN datasets.
Online Trajectory Planning and Force Control for Automation of Surgical Tasks

Automation of surgical tasks is expected to improve the quality of surgery. In this paper, we address two issues that must be resolved for automation of robotic surgery: online trajectory planning and force control under dynamic conditions. By leveraging demonstrations under various conditions, we model the conditional distribution of the trajectories given the task condition. This scheme enables generalization of the trajectories of spatial motion and contact force to new conditions in real time. In addition, we propose a force tracking controller that robustly and stably tracks the planned profile of the contact force by learning the spatial motion and contact force simultaneously. The proposed scheme was tested with bimanual tasks emulating surgical tasks that require online trajectory planning and force tracking control, such as tying knots and cutting soft tissues. Experimental results show that the proposed scheme enables planning of the task trajectory under dynamic conditions in real time. In addition, the performance of the force control schemes was verified in the experiments.Note to Practitioners—This paper addresses the problem of motion planning and control for automation of surgical tasks. In surgical tasks, it is necessary to manipulate objects under conditions where positions or shapes of objects often change during the task. Thus, trajectories for surgical tasks need to be planned and updated according to the change in the conditions in real time. In this paper, we propose a framework for learning both spatial motion and force profile from human experts. The proposed system can plan and update task trajectories in real time and robustly control the contact force under dynamic conditions. On the other hand, generalization of trajectories is limited to the conditions, which are close to the conditions where the demonstrations were performed. In the future work, we will investigate reinforcement learning approaches in order to enable autonomous improvement of the performance.