Miracle-dz/UniFAR-FTUs huggingface dataset:
Using a tablet application about nutrition in home care—Experiences and perspectives of healthcare professionals

Undernutrition is an extensive problem among patients in community care services. The literature identifies several barriers that hinder health professionals in identifying nutritional problems and providing nutrition interventions. We developed Appetitus, a tablet application (app) focused on nutrition for older adults. Patients used the app, advised by healthcare professionals. In this study with qualitative design, we explored experiences and perspectives of healthcare professionals who used Appetitus when providing home care. We interviewed 24 healthcare professionals individually and in focus groups. We subjected the data to qualitative content analysis. Healthcare professionals used Appetitus as a mediator in dialogues with patients about nutrition. Giving the older adults an active role in nutrition assessment afforded opportunities to strengthen their involvement in care. Registrations of food and drink consumption gave the healthcare professionals insight into patients' situations and revealed problems of which the healthcare professionals had not been aware. Based on their experience with Appetitus, healthcare professionals suggested using electronic tools to assess and document the nutritional situation of a larger patient group in home care. In future use of Appetitus, healthcare professionals' levels of knowledge and confidence when advising patients about nutrition must be emphasised and addressed. Barriers such as time constraints and limited continuity of care are also areas that require attention when new nutrition practices are implemented.
Willingness to Participate and Associated Factors in a Zika Vaccine Trial in Indonesia: A Cross-Sectional Study

One of the crucial steps during trials for Zika and other vaccines is to recruit participants and to understand how participants’ attitudes and sociodemographic characteristics affect willingness to participate (WTP). This study was conducted to assess WTP, its explanatory variables, and the impact of financial compensation on WTP in Indonesia. A health facility-based cross-sectional study was conducted in eleven regencies in the Aceh and West Sumatra provinces of Indonesia. Participants were recruited via a convenience sampling method and were interviewed. The associations between explanatory variables and WTP were assessed using a two-step logistic regression analysis. A total of 1,102 parents were approached, and of these 956 (86.8%) completed the interview and were included in analysis. Of those, 144 (15.1%) were willing to participate in a Zika vaccine trial without a financial compensation. In the multivariate analysis, WTP was tied to an age of more than 50 years old, compared to 20–29 years (odds ratio (OR): 5.0; 95% confidence interval (CI): 2.37–10.53), to being female (OR: 2.20; 95% CI: 1.11–4.37), and to having heard about Zika (OR: 2.41; 95% CI: 1.59–3.65). Participants’ WTP increased gradually with higher financial compensation. The rate of WTP increased to 62.3% at the highest offer (US$ 350.4), and those who were still unwilling to participate (37.7%) had a poorer attitude towards childhood vaccination. This study highlights that pre-existing knowledge about Zika and attitudes towards childhood vaccination are important in determining community members being willing to participate in a vaccine trial. Financial incentives are still an important factor to enhance participant recruitment during a vaccine trial.
Deficiency of cathepsin C ameliorates severity of acute pancreatitis by reduction of neutrophil elastase activation and cleavage of E-cadherin

Acute pancreatitis is characterized by premature intracellular protease activation and infiltration of inflammatory cells, mainly neutrophil granulocytes and macrophages, into the organ. The lysosomal proteases cathepsin B, D, and L have been identified as regulators of early zymogen activation and thus modulators of the severity of pancreatitis. Cathepsin C (CTSC, syn. dipeptidly-peptidase I) is a widely expressed, exo-cystein-protease involved in the proteolytic processing of various other lysosomal enzymes. We have studied its role in pancreatitis. We used CTSC-deleted mice and their WT littermates in two experimental models of pancreatitis. The mild model involved eight hourly caerulein injections and the severe model partial duct ligation. Isolated pancreatic acini and spleen-derived leukocytes were used for ex vivo experiments. CTSC is expressed in the pancreas and in inflammatory cells. CTSC deletion reduced the severity of pancreatitis (more prominently in the milder model) without directly affecting intra-acinar cell trypsin activation in vitro. The absence of CTSC reduced infiltration of neutrophil granulocytes impaired their capacity for cleaving E-cadherin in adherens junctions between acinar cells and reduced the activity of neutrophil serine proteases polymorphonuclear (neutrophil) elastase, cathepsin G, and proteinase 3, but not neutrophil motility. Macrophage invasion was not dependent on the presence of CTSC. CTSC is a regulator and activator of various lysosomal enzymes such as cathepsin B, D, and L. Its loss mitigates the severity of pancreatitis not by reducing intra-acinar cell zymogen activation but by reducing infiltration of neutrophil granulocytes into the pancreas. In this context one of its key roles is that of an activator of neutrophil elastase.
Post-translational and transcriptional dynamics – regulating extracellular vesicle biology

ABSTRACT Introduction: Extracellular vesicles (EVs) are secreted into their extracellular environment, contain a specific repertoire of cellular cargo, and represent a novel vehicle for cell–cell communication. Protein post-translational modifications (PTMs) are emerging as major effectors of EV biology and function, and in turn, regulate cellular signaling. Areas covered: Discovery and investigation of PTMs such as methylation, glycosylation, acetylation, phosphorylation, sumoylation, and many others has established fundamental roles for PTMs within EVs and associated EV function. The application of enrichment strategies for modifications, high-resolution quantitative mass spectrometry-based proteomics, and improved technological approaches have provided key insights into identification and characterization of EV-based PTMs. Recently, an overwhelming appreciation for the diversity of modifications, including post-transcriptional modifications, dynamic roles of these modifications, and their emerging interplay, including protein–protein, protein–lipid, protein–RNA, and variable RNA modifications, is emerging. At a cellular level, such interplay is essential for gene expression/genome organization, protein function and localization, RNA metabolism, cell division, and cell signaling. Expert commentary: The understanding of these modifications and interactions will provide strategies toward how distinct cargo is localized, sorted, and delivered through EVs to mediate intercellular function, with further understanding of such modifications and intermolecular interactions will provide advances in EV-based therapeutic strategies.
StructureNet: Inducing Structure in Generated Melodies

We present the StructureNet - a recurrent neural network for inducing structure in machine-generated compositions. This model resides in a musical structure space and works in tandem with a probabilistic music generation model as a modifying agent. It favourably biases the probabilities of those notes that result in the occurrence of structural elements it has learnt from a dataset. It is extremely ﬂexible in that it is able to work with any such probabilistic model, it works well when training data is limited, and the types of structure it can be made to induce are highly customis-able. We demonstrate through our experiments on a sub-set of the Nottingham dataset that melodies generated by a recurrent neural network based melody model are indeed more structured in the presence of the StructureNet.
An Automated Algorithm to Quantify Collagen Distribution in Aortic Wall

Arterial diseases including abdominal aortic aneurysm and atherosclerosis are biomechanical diseases characterized by significant changes in the structure and strength of the vessel wall. It is now established that local variations in fibrillar collagen and elastin matrix turnover is critical to arterial stiffening and progression of the disease. The collagen content in the aortic wall has nominally been quantified by biochemical assays and immunohistochemical analysis as the total amount because of the difficulty in separating the media and adventitia. In this work, we have developed an algorithm for automatic quantification of layer-specific collagen content from bright-field and polarized microscopic images of histological sections of mouse aorta stained with Picrosirius red (PSR) stain. The images were processed sequentially including separation of layers, erosion, segregation of regions, binarization, and quantification of pixel intensities to obtain collagen content in the media and adventitia separately. We observed that the automated algorithm rapidly and accurately quantified collagen content from a wide range of image quality compared with manual measurements particularly when the medial and adventitial layers overlap. Together, our algorithm will be of significant impact in the rapid, reliable, and accurate analyses of collagen distribution in histological sections of connective tissues.
Rosmarinic Acid, a Component of Rosemary Tea, Induced the Cell Cycle Arrest and Apoptosis through Modulation of HDAC2 Expression in Prostate Cancer Cell Lines

Rosmarinic acid (RA), a main phenolic compound contained in rosemary which is used as tea, oil, medicine and so on, has been known to present anti-inflammatory, anti-oxidant and anti-cancer effects. Histone deacetylases (HDACs) are enzymes that play important roles in gene expression by removing the acetyl group from histone. The aberrant expression of HDAC in human tumors is related with the onset of human cancer. Especially, HDAC2, which belongs to HDAC class I composed of HDAC 1, 2, 3 and 8, has been reported to be highly expressed in prostate cancer (PCa) where it downregulates the expression of p53, resulting in an inhibition of apoptosis. The purpose of this study is to investigate the effect of RA in comparison with suberoylanilide hydroxamic acid (SAHA), an HDAC inhibitor used as an anti-cancer agent, on survival and apoptosis of PCa cell lines, PC-3 and DU145, and the expression of HDAC. RA decreased the cell proliferation in cell viability assay, and inhibited the colony formation and tumor spheroid formation. Additionally, RA induced early- and late-stage apoptosis of PC-3 and DU145 cells in Annexin V assay and terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) assay, respectively. In western blot analysis, RA inhibited the expression of HDAC2, as SAHA did. Proliferating cell nuclear antigen (PCNA), cyclin D1 and cyclin E1 were downregulated by RA, whereas p21 was upregulated. In addition, RA modulated the protein expression of intrinsic mitochondrial apoptotic pathway-related genes, such as Bax, Bcl-2, caspase-3 and poly (ADP-ribose) polymerase 1 (PARP-1) (cleaved) via the upregulation of p53 derived from HDAC2 downregulation, leading to the increased apoptosis of PC-3 and DU145 cells. Taken together, treatment of RA to PCa cell lines inhibits the cell survival and induces cell apoptosis, and it can be used as a novel therapeutic agent toward PCa.
Stable and Efficient Policy Evaluation

Policy evaluation algorithms are essential to reinforcement learning due to their ability to predict the performance of a policy. However, there are two long-standing issues lying in this prediction problem that need to be tackled: off-policy stability and on-policy efficiency. The conventional temporal difference (TD) algorithm is known to perform very well in the on-policy setting, yet is not off-policy stable. On the other hand, the gradient TD and emphatic TD algorithms are off-policy stable, but are not on-policy efficient. This paper introduces novel algorithms that are both off-policy stable and on-policy efficient by using the oblique projection method. The empirical experimental results on various domains validate the effectiveness of the proposed approach.
Training Transfer Behaviors: The Roles of Trainee Confidence, Knowledge, and Work Attitudes

Transfer of training refers to the extent to which desired work behaviors are transferred to the workplace following training. This study evaluated training transfer ratings as a function of trainee variables following training (confidence and knowledge) and work attitudes and evaluations (job satisfaction and transfer climate). Consistent with the literature, positive associations with transfer were hypothesized. Training was developed to align transfer behaviors with organizational goals. Subsequently, a questionnaire was distributed to 109 employees of a natural foods grocery store. The data yielded partial support for hypotheses. Although trainee variables and job satisfaction were positively related to transfer of training, transfer climate was not. Also consistent with the literature, the frequency of transfer behaviors was fairly low, and varied as a function of department and employment status. Implications for theory and practice based on the findings are discussed.
Otosclerosis; clinical long term-perspectives

This thesis has assessed medical, technical and health-related aspects of otosclerosis from a long-term perspective. A retrospective clinical study was performed where 65 subjects who had previously undergone stapedectomy (1977-1979) were assessed. Twenty-eight Thirty years later a follow-up was conducted. In Paper I, hearing thresholds were studied. Thirty years after surgery the mean hearing impairment was comparable with the preoperative level. The hearing deterioration was mainly caused by sensorineural hearing loss which was significantly worse compared to an age and sex matched control population (ISO 7029). In Paper II, hearing aid use and satisfaction were analyzed. Almost all subjects (95%) would have benefitted from hearing aid rehabilitation, however only 54 % had been fitted with hearing aids. Subjects who had received hearing aids were generally everyday users (94 %) and were very satisfied with their hearing aids. In Paper III, hearing disability and health-related quality of life was assessed. The subjects experienced hearing problems, especially in complex listening situations and in localization of sounds. Health-related quality of life showed results comparable to that of the reference population. In Paper IV, 20 of the subjects were analyzed by multi-slice and cone-beam CT (MSCT, CBCT) to assess the applicability of CBCT in the assessment of otosclerosis. The study showed that CBCT was valid in the assessments and in many ways was equivalent to MSCT. Keywords; Otosclerosis, hearing loss, conductive, stapedectomy, hearing aid, health-related quality of life, hearing disability, SF-36, SSQ, IOI-HA, MSCT, CBCT ISBN 978-91-628-8617-2 http://hdl.handle. net/2077/31712
Multi-level Approximate Bayesian Computation

Approximate Bayesian Computation is widely used to infer the parameters of discrete-state continuous-time Markov networks. In this work, we focus on models that are governed by the Chemical Master Equation (the CME). Whilst originally designed to model biochemical reactions, CME-based models are now frequently used to describe a wide range of biological phenomena mathematically. We describe and implement an efficient multi-level ABC method for investigating model parameters. In short, we generate sample paths of CME-based models with varying time resolutions. We start by generating low-resolution sample paths, which require only limited computational resources to construct. Those sample paths that compare well with experimental data are selected, and the temporal resolutions of the chosen sample paths are recursively increased. Those sample paths unlikely to aid in parameter inference are discarded at an early stage, leading to an optimal use of computational resources. The efficacy of the multi-level ABC is demonstrated through two case studies.
Leveraging knowledge bases for future prediction with memory comparison networks

Making predictions about what might happen in the future is important for reacting adequately in many situations. For example, observing that “Man kidnaps girl” may have the consequence that “Man kills girl”. While this is part of common sense reasoning for humans, it is not obvious how machines can acquire and generalize over such knowledge. In this article, we propose a new type of memory network that can predict the next future event also for observations that are not in the knowledge base. We evaluate our proposed method on two knowledge bases: Reuters KB (events from news articles) and Regneri KB (events from scripts). For both knowledge bases, our proposed method shows similar or better prediction accuracy on unseen events (or scripts) than recently proposed deep neural networks and rankSVM. We also demonstrate that the attention mechanism of our proposed method can be helpful for error analysis and manual expansion of the knowledge base.
The Adaptive Filtering Algorithms for Engine’s Noise Cancellation in Speech Signals

The presence of noise superimposed on a signal limits the receiver’s ability to correctly identify the intended signal. The principal of adaptive noise cancellation is to acquire an estimation of the unwanted interfering signal and subtract it from the corrupted signal. Noise cancellation operation is controlled adaptively with the target of achieving improved signal to noise ratio. This paper describes the Least Mean Squares (LMS) adaptive filtering algorithm. The algorithm was implemented in Matlab and was tested for noise cancellation in speech signals.
Frame service delay analysis of IEEE 802.11 MAC protocol and its application in congestion control

For the problem that a traditional congestion signal such as the average length of a queue cannot indicate network congestion effectively in the ad hoc network,an analysis has been made of the frame service delay(FSD) of IEEE 802.11 MAC protocol,and the relation between the average FSD and the average length of the frame,the collision probability,and the number of saturated stations.Analytical results show that FSD increases sharply with the increase in transmission probability or the number of saturated stations if the transmitting probability of stations is larger than the critical one,and that FSD has a high sensitivity to the link congestion.Finally,the effectiveness of FSD as the congestion signal is validated by simulation.Compared with the average length of the queue,FSD can indicate network congestion more effectively.Together with TCP,the use of FSD as the congestion signal can prominently improve the throughput of TCP connection and decrease the ratio of packet loss.
Research on knowledge-based planning of storage space allocation in container yards

For storage space allocation on container yard,there are many kinds of rules in planning a container's location. For this characteristic,this paper proposed a knowledge-based storage space allocation method.Firstly,described the compo- sition of knowledge and its representation a knowledge-based model for storage space allocation,and established.This model was comprised of three parts:partition of allocation area,operation mode and rule match,the best slot selection.The applica- tion value of this method is verified by an actual example.
The Influence of Photodynamic Therapy on Tumor Cell S180

Today cancer is the second important factor of the death in the world. Most of the cancer patients are treated with standard therapies, including surgery, radiation and/or chemotherapy. These standard therapies are most efficient on the primary tumor, but in the case of disseminated disease, they are often not effective. Treatment of disease that has disseminated from the primary tumor and metastasized to distant sites has promoted the investigation of immunotherapeutic strategies for cancer, and has been a major area of research over the last couple of decades. Chemotherapy and radiotherapy, standard therapies, are the main treatments for majority of cancer patients. Our studies demonstrate that ALA-HMME-PDT has a role in enhanced the quality of life and lengthens survival in mice infected by sarcoma 180. The reported method is hardly implemented but it possible in any clinical situation where PDT is needed. These therapies are most efficient in bearing the tumor in its first process of formation. Currently, the hot topic of discussion and research in the cancer arena is photodynamic Therapy (PDT). This type of therapy is an emerging channel of treatment that is very successful in eradicating cancer, with few side effects. The effectiveness of photodynamic therapy on the sarcoma treating process in mice by using ALA and HMME photosensitizers is investigated by this study. Many factors help us determine effectiveness of PDT including concentration of the sensitizer, absorption of light energy and accessibility of molecular oxygen in the target tissue during light irradiation, besides intrinsic sensitivity of target tissue.
Male Assistance in Parental Care Does Not Buffer Against Detrimental Effects of Maternal Inbreeding on Offspring

The severity of inbreeding depression often varies across environments and recent work suggests that social interactions can aggravate or reduce inbreeding depression. For example, stressful interactions such as competition can exacerbate inbreeding depression, whereas benign interactions such as parental care can buffer against inbreeding depression in offspring. Here, we test whether male assistance in parental care can buffer against the detrimental effects of maternal inbreeding on offspring fitness in the burying beetle Nicrophorus vespilloides. Our results confirm that maternal inbreeding had detrimental effects on offspring survival. However, we found no evidence that male assistance in parental care buffered against those effects on offspring fitness. Outbred females benefitted from male assistance, gaining more weight over the breeding attempt when assisted by a male. In contrast, inbred females did not benefit from male assistance, gaining as much weight regardless of whether they were assisted by a male or not. Surprisingly, we find that males gained more weight during the breeding attempt when mated to an inbred female, suggesting that males benefitted from assisting an inbred female partner in terms of their weight gain. Overall, our findings suggest that parental care or other benign social interactions may not always buffer against detrimental effects of inbreeding depression.
3D Printing—Encompassing the Facets of Dentistry

This narrative review presents an overview on the currently available 3D printing technologies and their utilization in experimental, clinical and educational facets, from the perspective of different specialties of dentistry, including oral and maxillofacial surgery, orthodontics, endodontics, prosthodontics, and periodontics. It covers research and innovation, treatment modalities, education and training, employing the rapidly developing 3D printing process. Research-oriented advancement in 3D printing in dentistry is witnessed by the rising number of publications on this topic. Visualization of treatment outcomes makes it a promising clinical tool. Educational programs utilizing 3D-printed models stimulate training of dental skills in students and trainees. 3D printing has enormous potential to ameliorate oral health care in research, clinical treatment, and education in dentistry.