Miracle-dz/UniFAR-FTUs huggingface dataset:
Fingerprint image enhancement using filtering techniques

Extracting minutiae from fingerprint images is one of the most important steps in automatic fingerprint identification and classification. Minutiae are local discontinuities in the fingerprint pattern, mainly terminations and bifurcations. In this work we propose two methods for fingerprint image enhancement. The first one is carried out using local histogram equalization, Wiener filtering, and image binarization. The second method use a unique anisotropic filter for direct grayscale enhancement. The results achieved are compared with those obtained through some other methods. Both methods show some improvement in the minutiae detection process in terms of either efficiency or time required.
Neuropsychological and functional correlates of clock‐drawing test in elderly institutionalized patients with schizophrenia

Background: There has been a growing need for a cognitive assessment tool that can be used for older adults with schizophrenia in clinical settings. The clock‐drawing test (CDT) is a brief cognitive test that covers a wide range of cognitive function. Although it is widely used to assess patients with dementia, limited data are available on its usefulness in older patients with schizophrenia. Thus, we investigated the psychometric properties of the CDT and their relationship with life functions to examine the test's usefulness for assessing cognitive function in older adults with schizophrenia.
Strategies for improving the efficiency of semiconductor metal oxide photocatalysis

Photocatalysis is of significant interest for a wide range of applications related to energy and environment, such as pollutant degradation and hydrogen production. We will provide a review of the relationship between photocatalyst properties and its photocatalytic performance, as well as the strategies for the enhancement of photocatalytic activity, in particular under solar/ambient/visible illumination. Common applications of photocatalysts will then be reviewed, and we will summarize existing problems and areas requiring further improvements.
The lived experience of recovery during the first 6 months after colorectal cancer surgery

AIMS AND OBJECTIVES To describe the lived experience of recovery during the first 6 months after colorectal cancer surgery. BACKGROUND Colorectal cancer is the third most common cancer diagnosis worldwide. Early discharge places demands on healthcare professionals to prepare patients for their return home and to provide them with appropriate support throughout the recovery process. This requires knowledge of what it is like to recover from colorectal cancer surgery. DESIGN A qualitative phenomenological design was used to describe the structure of recovery after colorectal cancer surgery. METHODS Ten patients recovering from colorectal cancer surgery were interviewed at one month and six months after surgery. The descriptive phenomenological method by Giorgi was used throughout the study. RESULTS Postoperative recovery was described as a progressive process. This process was accompanied by experiences of physical powerlessness, difficulties with food intake, altered bowel function and dependency on others. The experiences were most intense at the beginning of the recovery but disappeared as time went by and normality in life returned. CONCLUSION While recovering from colorectal cancer surgery, patients experience obstacles that impede their ability to live life as normal. Six months after surgery, those experiences disappear or become adjusted to being part of normal life. RELEVANCE TO CLINICAL PRACTICE Patients should be provided with information about the expected postoperative recovery before discharge from hospital. The need for professional support appears to be most frequently needed in early recovery, but it should be considered on an individual basis.
Ocean One: A Robotic Avatar for Oceanic Discovery

The promise of oceanic discovery has long intrigued scientists and explorers, whether with the idea of studying underwater ecology and climate change or with the hope of uncovering natural resources and historic secrets buried deep in archaeological sites. This quest to explore the oceans requires skilled human access, yet much of the oceans are inaccessible to human divers; nearly ninetenths of the ocean floor is at 1 km or deeper [1]. Accessing these depths is imperative since factors such as pollution and deep-sea trawling threaten ecology and archaeological sites. While remotely operated vehicles (ROVs) are inadequate for the task, a robotic avatar could go where humans cannot and still embody human intelligence and intentions through immersive interfaces.
#Autism Versus 299.0: Topic Model Exploration of Multimodal Autism Data

Though prevalence and awareness for Autism Spectrum Disorder (ASD) has steadily increased, a true understanding is hard to reach because of the behavior-based nature of the diagnosis and the heterogeneity of its manifestations. Parents and caregivers often informally discuss symptoms and behaviors they observe from their children with autism through online medical forums, contrasting the more traditional and structured text of electronic medical records collected by doctors. We modify an anchor word driven topic model algorithm originally proposed by Arora et al. (2012a) to elicit and compare the medical concept topics, or “themes” from both modes of data: the novel data set of posts from autism-specific online medical forums and electronic medical records. We present methods to extract relevant medical concepts from colloquially written forum posts through the use of choice sections of the consumer health vocabulary and other filtering techniques. In order to account for the sparsity of concept data, we propose and evaluate a more robust approach to selecting anchor words that takes into account variance and inclusivity. This approach that combines concept and anchor words selection seeds the discussion about how unstructured text can influence and expand understanding of the enigmatic disorder, autism, and how these methods can be applied to similar sources of texts to solve other problems. The code and its instructions can be found at https://github.com/jming/thesis. Any questions or comments can be directed to joy.c. ming@gmail.com.
Characterization of the Adaptive Amoxicillin Resistance of Lactobacillus casei Zhang by Proteomic Analysis

Amoxicillin is one of the most commonly prescribed antibiotics for bacterial infections and gastrointestinal disorders. To investigate the adaptation of Lactobacillus (L.) casei Zhang to amoxicillin stress, an iTRAQ-based comparative proteomic analysis was performed to compare the protein profiles between the parental L. casei Zhang and its amoxicillin-resistant descendent strains. Our results revealed a significant increase in the relative expression of 38 proteins (>2.0-folds, P < 0.05), while the relative expression of 34 proteins significantly decreased (<−2.0-folds, P < 0.05). The amoxicillin-resistant descendent strain exhibited marked alterations in carbohydrate and amino acid metabolism. Moreover, certain components involving in membrane metabolism were activated. The differences in the proteomic profiles between the two strains might explain the enhanced stress resistance of the adapted bacteria.
CheckInside: a fine-grained indoor location-based social network

Existing location-based social networks (LBSNs), e.g. Foursquare, depend mainly on GPS or network-based localization to infer users' locations. However, GPS is unavailable indoors and network-based localization provides coarse-grained accuracy. This limits the accuracy of current LBSNs in indoor environments, where people spend 89% of their time. This in turn affects the user experience, in terms of the accuracy of the ranked list of venues, especially for the small-screens of mobile devices; misses business opportunities; and leads to reduced venues coverage. In this paper, we present CheckInside: a system that can provide a fine-grained indoor location-based social network. CheckInside leverages the crowd-sensed data collected from users' mobile devices during the check-in operation and knowledge extracted from current LBSNs to associate a place with its name and semantic fingerprint. This semantic fingerprint is used to obtain a more accurate list of nearby places as well as automatically detect new places with similar signatures. A novel algorithm for handling incorrect check-ins and inferring a semantically-enriched floorplan is proposed as well as an algorithm for enhancing the system performance based on the user implicit feedback. Evaluation of CheckInside in four malls over the course of six weeks with 20 participants shows that it can provide the actual user location within the top five venues 99% of the time. This is compared to 17% only in the case of current LBSNs. In addition, it can increase the coverage of current LBSNs by more than 25%.
A Facile Approach to Tune the Electrical and Thermal Properties of Graphene Aerogels by Including Bulk MoS2

Graphene aerogels (GAs) have attracted extensive interest in diverse fields, owing to their ultrahigh surface area, low density and decent electrical conductivity. However, the undesirable thermal conductivity of GAs may limit their applications in energy storage devices. Here, we report a facile hydrothermal method to modulate both the electrical and thermal properties of GAs by including bulk molybdenum disulfide (MoS2). It was found that MoS2 can help to reduce the size of graphene sheets and improve their dispersion, leading to the uniform porous micro-structure of GAs. The electrical measurement showed that the electrical conductivity of GAs could be decreased by 87% by adding 0.132 Vol % of MoS2. On the contrary, the thermal conductivity of GAs could be increased by ~51% by including 0.2 vol % of MoS2. The quantitative investigation demonstrated that the effective medium theories (EMTs) could be applied to predict the thermal conductivity of composite GAs. Our findings indicated that the electrical and thermal properties of GAs can be tuned for the applications in various fields.
Virtual agent-mediated appraisal training: a single case series among Dutch firefighters

ABSTRACT Background: First responders are a prime example of professionals that are at a high risk of being exposed to traumatic experiences. Reappraisal as a coping strategy might help first responders to better cope with their emotional responses to traumatic events. Objective: This study investigated the effects of repeated sessions of a digital reappraisal training among seven firefighters. The training consisted of four sessions supported by a virtual agent, conducted at home or at work, over a two-week period in a single case series. Method: Sixteen data points were collected from each participant in the eight days pre- and post-training. Results: Significantly more themes were used at post-training than at pre-training, implying more flexibility and confirming the main hypothesis of the study. Negative side effects were not reported during or in the week after the training. Conclusions: More controlled studies into the short- and long-term effects of a training of this nature are needed. Furthermore, it provides a reference for developers in this field.
Harmonium: Asymmetric, Bandstitched UWB for Fast, Accurate, and Robust Indoor Localization

We introduce Harmonium, a novel ultra-wideband RF localization architecture that achieves decimeter-scale accuracy indoors. Harmonium strikes a balance between tag simplicity and processing complexity to provide fast and accurate indoor location estimates. Harmonium uses only commodity components and consists of a small, inexpensive, lightweight, and FCC-compliant ultra-wideband transmitter or tag, fixed infrastructure anchors with known locations, and centralized processing that calculates the tag's position. Anchors employ a new frequency-stepped narrowband receiver architecture that rejects narrowband interferers and extracts high-resolution timing information without the cost or complexity of traditional ultra-wideband approaches. In a complex indoor environment, 90% of position estimates obtained with Harmonium exhibit less than 31 cm of error with an average 9 cm of inter-sample noise. In non-line-of-sight conditions (i.e. through-wall), 90% of position error is less than 42 cm. The tag draws 75 mW when actively transmitting, or 3.9 mJ per location fix at the 19 Hz update rate. Tags weigh 3 g and cost $4.50 USD at modest volumes. Harmonium introduces a new design point for indoor localization and enables localization of small, fast objects such as micro quadrotors, devices previously restricted to expensive optical motion capture systems.
The Human Cathelicidin LL-37 Host Defense Peptide Upregulates Tight Junction-Related Proteins and Increases Human Epidermal Keratinocyte Barrier Function

Both psoriasis and atopic dermatitis (AD) are not only associated with an impaired stratum corneum barrier, but also with abnormal expression of the tight junction (TJ) proteins. Because host defense peptides, including LL-37, are overexpressed in lesional psoriatic skin but are downregulated in lesional AD skin, we hypothesized that LL-37 might regulate the TJ function in keratinocytes. We demonstrated that LL-37 selectively increased the expression of several claudins and occludin, and enhanced their membrane distribution. Furthermore, LL-37 elevated the transepithelial electrical resistance while reducing the paracellular permeability of keratinocyte layers, and this activity was weakened by the claudin inhibitor ochratoxin A. A characterization of the molecular mechanism underlying the regulation of the TJ barrier by LL-37 revealed that LL-37 induced the activation of the Rac1, atypical PKC, glycogen synthase kinase-3 and PI3K pathways, and the specific inhibition of these pathways reversed the LL-37-mediated regulation of TJ function. In addition, LL-37 enhanced the expression of differentiation markers under the control of ochratoxin A, suggesting an association between LL-37-induced TJ function and keratinocyte differentiation. These data provide novel evidence that, in addition to its antimicrobial and other immunoregulatory functions, LL-37 contributes to cutaneous immunity by strengthening the skin's barrier function.
GigaTensor: scaling tensor analysis up by 100 times - algorithms and discoveries

Many data are modeled as tensors, or multi dimensional arrays. Examples include the predicates (subject, verb, object) in knowledge bases, hyperlinks and anchor texts in the Web graphs, sensor streams (time, location, and type), social networks over time, and DBLP conference-author-keyword relations. Tensor decomposition is an important data mining tool with various applications including clustering, trend detection, and anomaly detection. However, current tensor decomposition algorithms are not scalable for large tensors with billions of sizes and hundreds millions of nonzeros: the largest tensor in the literature remains thousands of sizes and hundreds thousands of nonzeros. Consider a knowledge base tensor consisting of about 26 million noun-phrases. The intermediate data explosion problem, associated with naive implementations of tensor decomposition algorithms, would require the materialization and the storage of a matrix whose largest dimension would be ≈7 x 1014; this amounts to ~10 Petabytes, or equivalently a few data centers worth of storage, thereby rendering the tensor analysis of this knowledge base, in the naive way, practically impossible. In this paper, we propose GIGATENSOR, a scalable distributed algorithm for large scale tensor decomposition. GIGATENSOR exploits the sparseness of the real world tensors, and avoids the intermediate data explosion problem by carefully redesigning the tensor decomposition algorithm. Extensive experiments show that our proposed GIGATENSOR solves 100 times bigger problems than existing methods. Furthermore, we employ GIGATENSOR in order to analyze a very large real world, knowledge base tensor and present our astounding findings which include discovery of potential synonyms among millions of noun-phrases (e.g. the noun 'pollutant' and the noun-phrase 'greenhouse gases').
Comparison of loads for wind turbine down-regulation strategies

For wind farm active power setpoint tracking, both farm level and turbine level down-regulation strategies should to be optimized considering turbine health condition. Several down-regulation strategies are chosen to analyse the wind turbine load performance according to different wind speed and power reference. In this paper we suggest appropriate down-regulation strategy to control wind turbine for active power reference tracking. we compare four different down-regulation strategies, namely Const-Ω, Const-λ, Max-Ω and Min-Ct and discuss the loads on main components and downstream wind speed by presenting analysis of several wind scenarios and simulation in full-range operation.
Capture the car!: qualitative in-situ methods to grasp the automotive context

In terms of human computer interaction (HCI), the car interior is a space, which can be divided into three areas: the driver's area, the front seat area, and the back seat area. So far HCI researchers have primary focused on the driver, and how in-car electronic devices can be designed to assist the driver in order to increase safety and comfort. We propose that for investigating interactive technology in the car in a holistic way, all three areas have to be taken into account. For that purpose we argue for an increased usage of qualitative in-situ studies, which have been hardly applied in automotive user interface research. So far the HCI community has mainly focused on laboratory studies utilizing driving simulators. Despite the broad range of available field study methods, such as ethnographic and self-reporting studies, the adaption of these methods for the automotive context is challenging due to the specific characteristics of this environment. For instance, cars provide only very limited space, the environment is constantly changing while driving and the driver must not be distracted from driving safely. As a consequence, a lack of experience exists, on how in-situ methods should be applied to cars. In this paper we describe three qualitative in-situ studies, we conducted to research the driver, the front seat passenger, and the rear seat passenger spaces. All three studies used a different method tailored to fit these three areas best. To share our experiences and insights we discuss the strengths and pitfalls of each method.
Achievable Information Rates for Fiber Optics: Applications and Computations

In this paper, achievable information rates (AIR) for fiber optical communications are discussed. It is shown that AIRs such as the mutual information and generalized mutual information are good design metrics for coded optical systems. The theoretical predictions of AIRs are compared to the performance of modern codes including low-parity density check and polar codes. Two different computation methods for these AIRs are also discussed: Monte-Carlo integration and Gauss-Hermite quadrature. Closed-form ready-to-use approximations for such computations are provided for arbitrary constellations and the multidimensional AWGN channel. The computation of AIRs in optical experiments and simulations is also discussed.
Moderate impact of full‐term pregnancy on estimated peak oxygen uptake, physical activity and perceived health

Objective. To study the impact of pregnancy on estimated peak oxygen uptake (), physical activity and perceived health. Design. Prospective cohort study. Setting. Maternal health centers. Population. A cohort of pregnant women. Methods. Cycle ergometer test and questionnaires in early pregnancy and 5 months postpartum. Main outcome measures. , physical activity and perceived health. Results. Regular physical activity was reported by a successively lower proportion of women as pregnancy advanced but the proportion was regained postpartum. Despite this the difference between average absolute in early pregnancy and postpartum of 2.44 and 2.42 l/minute, respectively, was not significant. The adjusted absolute in early pregnancy successively increased with age to a maximum at 35 years, after which it decreased and among women of the same age the time between 8 and 12 weeks lowered the by 0.130 l/minute. With the Short Form 36 (SF‐36) questionnaire in early pregnancy the women scored their mean mental health to 72.0 and mean physical health to 79.7. At the postpartum appointment these scores were higher (p < 0.0001). Absolute and relative in early pregnancy were positively correlated to the variation of SF‐36′s mean physical health in early pregnancy (p < 0.0001) and postpartum (p < 0.0001). Conclusions. Pregnancy had a moderate influence on physical fitness and perceived health half a year postpartum despite less regular physical activity during pregnancy. in early pregnancy was positively correlated to perceived physical health.
Inducing shortcuts on a mobile phone interface

Due to size restrictions, mobile phone user interfaces are often difficult to use[8]. In this short paper, we investigated inducing shortcuts to replace the sequence of actions required to complete common tasks on a mobile phone. In particular, we used mobile phone interaction data to evaluate several methods for inducing shortcuts. We considered the balance between maximising interface efficiency and shortcuts that remained stable and hence predictable.
The Effect of Virtual Reality and Tetra-Ataxiometric Posturography Programs on Stroke Patients With Impaired Standing Balance

Objective To investigate the effect of virtual reality (VR) and a tetra-ataxiometric posturography (Tetrax) program on stroke patients with impaired standing balance. Methods Thirty acute stroke patients with impaired standing balance were recruited and randomly assigned to a VR, Tetrax, or control group. All patients received conventional balance training as a baseline; and VR and Tetrax patients received VR or Tetrax treatment, in addition. The primary outcome measures to evaluate the overall standing balance were the Berg Balance Scale (BBS) and the falling index (FI). The secondary outcome measures were the stability index (SI) and the weight distribution index (WDI), which were used to evaluate the balance status according to specific body positions. The FI, SI, and WDI were measured using the Tetrax instrument. Results The BBS and FI scores were improved in all groups, with no significant differences between groups. In open-eyed positions, the VR group showed significantly greater improvement in SI and WDI scores than the control group (p<0.017). In closed-eyed positions, the Tetrax group showed significantly greater improvement in SI and WDI scores than the control group (p<0.017). Conclusion The inclusion of VR and Tetrax programs did not lead to an overall benefit in balance. VR and Tetrax did, however, demonstrate a benefit in specific positions. A Tetrax program may benefit patients with abnormal proprioceptive function, whereas a VR program may benefit patients with normal sensory function.