Miracle-dz/UniFAR-FTUs huggingface dataset:
Occurrence and Timing of Advance Care Planning in Persons With Dementia in General Practice: Analysis of Linked Electronic Health Records and Administrative Data

Background Advance care planning (ACP) is a process of communication in which patients and family caregivers discuss preferences for future care with the healthcare team. For persons with dementia, it is crucial to timely engage in ACP. Therefore, we study ACP in dementia using electronic health record data. This study aims to determine how often ACP conversations are recorded, analyze time from dementia diagnosis until the first recorded conversation and time from the first recorded conversation to death, and analyze which factors are associated with the timing of ACP. Methods Electronic records of 15,493 persons with dementia in Dutch general practice between 2008 and 2016 were linked to national administrative databases. ACP conversations and indicators of health deficits to determine frailty were obtained from electronic records coded with the International Classification of Primary Care. Socio-demographic characteristics were derived from the national population registry managed by Statistics Netherlands. Date of death was derived from the Personal Records Database (2008–2018). Results ACP was recorded as such as 22 (95% CI, 20–23) first conversations per 1,000 person-years of follow-up. The hazard ratio (HR) for the first conversation increased every year after dementia diagnosis, from 0.01 in the first year to 0.07 in the 7th and 8th year after diagnosis. Median time from a first conversation to death was 2.57 years (95% CI, 2.31–2.82). Migrant status [non-Western vs. Western (HR 0.31, 95% CI, 0.15–0.65)] was significantly associated with a longer time from dementia diagnosis to the first conversation. Being pre-frail (HR 2.06, 95% CI, 1.58–2.69) or frail (HR 1.40, 95% CI, 1.13–1.73) vs. non-frail was significantly associated with a shorter time from dementia diagnosis to the first ACP conversation. Conclusion ACP conversations in Dutch general practice were rare for persons with dementia, or was rarely recorded as such. In particular among persons with a non-Western migration background and those who are non-frail, it started long after diagnosis. We advise further research into public health and practical strategies to engage persons with dementia with a non-Western migration background and non-frail persons early in the disease trajectory in ACP.
Continuous Magnesium Sulfate Infusions for Status Asthmaticus in Children: A Systematic Review

Objectives Magnesium sulfate is a second-tier therapy for asthma exacerbations in children; guidelines recommend a single-dose to improve pulmonary function and decrease the odds of admission to the in-patient setting. However, many clinicians utilize prolonged magnesium sulfate infusions for children with refractory asthma. The purpose of this review is to describe the efficacy and safety of magnesium sulfate infusions administered over ≥ 1 h in children with status asthmaticus. Methods Medline was searched using the keywords “magnesium sulfate” and “children. ” Articles evaluating the use of magnesium sulfate infusions for ≥1 h published between 1946 and August 2021 were included. Published abstracts were not included because of lack of essential details. All articles were screened by two reviewers. Results Eight reports including 447 children were included. The magnesium regimens evaluated included magnesium delivered over 1 h (n = 148; 33.1%), over 4–5 h (n = 105; 23.5%), and over >24 h (n = 194; 43.4%). Majority of patients received a bolus dose of 25–75 mg/kg/dose prior to initiation of a prolonged infusion (n = 299; 66.9%). For the patients receiving magnesium infusions over 4–5 h, the dosing regimen varied between 40 and 50 mg/kg/h. For those receiving magnesium infusions >24 h, the dosing varied between 18.4 and 25 mg/kg/h for a duration between 53.4 and 177.5 h. Only three reports including 186 patients (41.6%) included an evaluation of clinical outcomes including evaluation of lung function parameters, reduction in PICU transfers, and/or decrease in emergency department length of stay. Five reports including 261 patients (58.4%) evaluated magnesium serum concentrations. In most reports, the goal concentrations were between 4 and 6 mg/dL. Only 3 (1.1%) out of the 261 patients had supratherapeutic magnesium concentrations. The only reports finding adverse events attributed to magnesium were noted in those receiving infusions for >24 h. Clinically significant adverse events included hypotension (n = 74; 16.6%), nausea/vomiting (n = 35; 7.8%), mild muscle weakness (n = 22; 4.9%), flushing (n = 10; 2.2%), and sedation (n = 2; 0.4%). Conclusion Significant variability was noted in magnesium dosing regimens, with most children receiving magnesium infusions over >4 h. Most reports did not assess clinical outcomes. Until future research is conducted, the use of prolonged magnesium sulfate infusions should be reserved for refractory asthma therapy.
Resource monitoring with wireless sensor networks and satellite

Effective management of natural environment relies on acquiring accurate and detailed information in a timely manner. The technology advancements in the sensing, communication and processing fields have made it possible to capture the events of interest in the physical world from remote locations. The WiSE (Wireless Internet Sensing Environment) Project is a multi-disciplinary activity funded by the RCUK dot.rural Digital Economy Hub. It has been designed to facilitate the deployment of cameras and sensors to remotely monitor an area of interest in any weather condition. The platform is solar powered and fully autonomous. A satellite unit enables deployment to the remotest part of the world and yet provides access to data via the Internet.
Evaluating soundscape intentions in landscape architecture: a study of competition entries for a new cemetery in Järva, Stockholm

While soundscape is increasingly acknowledged within landscape planning and design discourse, there is little research that clarifies how soundscapes are actually dealt with in landscape architecture practice – partly owing to methodological insufficiencies. This paper, therefore, describes a model for evaluating soundscape treatment in landscape design proposals, focusing on three key aspects. With the dual aim of testing the model, and learning more about how soundscape is approached in practice, the paper spotlights a major design competition for a new cemetery in Sweden. The model proved fruitful and easy to apply. It showed that only limited attention was paid to soundscape in the competition as a whole, and was a useful means of pinpointing proposals where soundscape was fully considered as a design feature; one competition entry that did so is described in the paper. Discussions cover design practice, trends in the competition and model application.
Statistical modeling and localization of nonrigid and articulated shapes

An articulated object can be loosely defined as a structure composed of links and joints. The human body is a good example of a nonrigid, articulated object. Localizing body shapes in still images remains a fundamental problem in computer vision, with potential applications in surveillance, video annotation, HCI, and entertainment. This thesis explores a 2D model-based approach to this problem. We start from a fixed viewpoint scenario (side-view walking) by introducing a landmark-based model of the body contours. Several image cues are combined in a Bayesian frame-work, including edge gradient, silhouette, skin color, and region similarity. The model is arranged into a sequential structure, enabling simple yet effective spatial inference through Sequential Monte Carlo (SMC). Next, we extend the system to situations where the viewpoint of the human target is unknown. To accommodate large viewpoint changes, a mixture of view-dependent models is employed. Each model is decomposed based on parts, with anthropometric constraints and self-occlusion explicitly treated. Inference is done again by SMC, searching in parallel with dynamic resource allocation. Finally, we study body localization in a generic setting: single image, arbitrary pose, and arbitrary viewpoint. The proposed solution is a hybrid search facilitated by a 3-level hierarchical decomposition of the model. We first fit a simple tree-structured model by Dynamic Programming (DP). The output is a series of proposal maps that encode the probabilities of partial body configurations. Next, we fit a mixture of view-dependent models by SMC, which handles self-occlusion and large viewpoint changes. DP and SMC search in opposite directions such that the DP proposals are utilized effectively to initialize and guide the SMC inference. This combination of deterministic and stochastic search ensures both the robustness and efficiency of DP, and the accuracy of SMC. Finally, we fit an expanded mixture model with increased landmark density through local optimization. The models were trained on a large number of gait images. Extensive tests on cluttered images with varying poses including walking, dancing and various types of sports activities demonstrate the feasibility of the proposed approach.
Generative Adversarial Networks in Brain Imaging: A Narrative Review

Artificial intelligence (AI) is expected to have a major effect on radiology as it demonstrated remarkable progress in many clinical tasks, mostly regarding the detection, segmentation, classification, monitoring, and prediction of diseases. Generative Adversarial Networks have been proposed as one of the most exciting applications of deep learning in radiology. GANs are a new approach to deep learning that leverages adversarial learning to tackle a wide array of computer vision challenges. Brain radiology was one of the first fields where GANs found their application. In neuroradiology, indeed, GANs open unexplored scenarios, allowing new processes such as image-to-image and cross-modality synthesis, image reconstruction, image segmentation, image synthesis, data augmentation, disease progression models, and brain decoding. In this narrative review, we will provide an introduction to GANs in brain imaging, discussing the clinical potential of GANs, future clinical applications, as well as pitfalls that radiologists should be aware of.
FEATURE MATCHING FOR TRAFFIC SIGN BOARD RECOGNITION

: Traffic safety is a complicated problem which requires careful designing and planning to develop an ideal solution. Traffic rules are implemented by the government to safeguard the public for a harmonious society and these rules are implemented using traffic signs. The general public is expected to identify, interpret and follow the traffic rules and signs. Failing to understand these signs would result in undesired consequences. An autonomous system in a car which performs detection, recognition, interpretation and gives warning to the motorist would help in reducing the number of accidents. In the proposed system, we use MATLAB to implement the recognition of traffic signs using the images captured and this forms a part of Driver Assistance system. Our system works in real time environment with high detection accuracy of more than 90% in different lighting conditions in the day and on partial damaged sign boards.
Adherence to Therapy in Glaucoma Treatment—A Review

Glaucoma is a chronic disease and the second leading cause of irreversible vision loss worldwide, whose initial treatment consists of self-administered topical ocular hypotensive eyedrops. Adherence with glaucoma medications is a fundamental problem in the care of glaucoma patients as up to 50% of patients fail to receive the intended benefits of the treatment. The literature has identified many barriers to patients’ compliance, from factors depending on the type of medication administered, communication between physician and patients, to factors dependent on patients’ behaviour and lifestyle. Failure to take medication as prescribed increases the risk that patients will not receive the desired benefit, which often leads to a worsening of the disease. Our aim is to synthesize the methods used for measuring adherence of patients to glaucoma therapy and the interventions used for addressing adherence, laying emphasis on a patient-centred approach, taking time to educate patients about their chronic disease and to assess their views on treatment.
A wide band distributed dual gate HEMT mixer

The authors present the systematic design, fabrication, and evaluation of a distributed wideband monolithic mixer using dual-gate HEMTs (high-electron-mobility transistors). The circuit was fabricated on an Al-GaAs-GaAs heterostructure wafer. The measurement results show that the mixer operates from 5 to 18 GHz with a conversion loss from 3 to 5 dB. This is believed to be the first reported wideband distributed mixer using dual-gate HEMT devices. The mixer chips developed are key components for EW (electronic warfare) applications. <<ETX>>
Anomaly Detection in Heart Disease Using a Density-Based Unsupervised Approach

Cardiovascular disease is one of the most common diseases in the modern world, which, if diagnosed early, can greatly reduce the damage to the patient. Diagnosis of heart disease requires great care, and in some cases, the process can be disrupted by human error. Machine learning methods, especially data mining, have gained international acceptance in almost all aspects of life, especially the prediction of heart disease. On the other hand, datasets related to heart patients have many biological features that most of these features do not have a direct impact on diagnosis. By removing redundant features from the dataset, in addition to reducing computational complexity, the accuracy of heart patients’ predictions can also be increased. This paper presents a density-based unsupervised approach to the diagnosis of abnormalities in heart patients. In this method, the basic features in the dataset are first selected based on the filter-based feature selection approach. Then, the DBSCAN clustering method with adaptive parameters has used to increase the clustering accuracy of healthy instances and to determine abnormal instances as cardiac patients. Partition clustering methods suffer from the selection of the number of clusters and the initial central points and are very sensitive to noise. The DBSCAN method solves these problems by creating density-based clusters, but the selection of the neighborhood radius threshold and the number of connected points in the neighborhood remains unresolved. In the proposed method, these two parameters are selected adaptively to achieve the highest accuracy for the diagnosis and prediction of heart patients. The results of the experiments show that the accuracy of the proposed method for predicting heart patients is approximately 95%, which has improved in comparison with previous methods.
An advanced integrated avalanche photodiode with Si and Ge material

An advanced avalanche photodiode (APD) was put forword which was integrated by the Si Separate Absorption, Charge, Multiplication (SACM) and Ge SACM APDs. This advanced APD has enlarged the detected wavelength range to 200-1 400 nm. Furthermore, the key parameters which were used to characterize the APD performance, such as the electric field distribution, the dark current and photocurrent, the gain, and the sensitivity of the APD were researched. The simulation results demonstrated that the breakdown voltage of the advanced APD is 145 V, the peak response is 22 A/W at 900 nm wavelength as cathode is 140 V, and the current gain of the advanced APD could get 50 at 400 nm wavelength before breakdown. The fabrication process was also discussed.
Securing Performance Of The Network In View Selective Drops

We're concerned in combating an insider attack and thinking about complexity of discovering happening of selective packet drops and recognize malicious node which are responsible for such drops. We develop accurate formula for recognition of selective packet drops which are produced by insider attackers. For making certain of computation of correlations, we create a homomorphic straight line authenticator that's on public auditing design basis that enables the detector to verify honesty of packet loss information that is as stated by nodes. In broad wireless means, link errors are relatively important, and may not be significantly lesser than packet shedding rate of insider attacker hence insider attacker can hide in backdrop of harsh funnel conditions. Within our work during study of packet sequence losses inside the network, we're concerned in figuring out whether losses come from way of link errors simply, otherwise by collective aftereffect of link errors in addition to malicious drop. This arrangement is privacy preserving, and sustains low communication in addition to storage spending. Our formula additionally provides honest in addition to openly verifiable decision statistics as proof to keep recognition decision.
Leaf and Root-growth Characteristics Contributing to Salt Tolerance of Backcrossed Pepper (Capsicum annuum L.) Progenies under Hydroponic Conditions

The aim of this study was to determine the genotypic differences in salt tolerance of third back-crossed peeper progenies and their respective parents through examining the changes in the shoot growth at agronomical, root growth at morphological and leaf development at physiological levels under salt stress. A hydroponic experiment was conducted by using an aerated Deep-Water Culture (DWC) technique in a controlled growth chamber of Erciyes University, Agricultural Faculty in Kayseri, Turkey. Five pepper plants (BC3-1, BC3-2, BC3-3, BC3-4, BC3-5) were selected from the third backcrossed (BC3) progenies of Sena and Kopan. Plants were grown in 8 L pots filled continuously aerated nutrient solution under at two electrical conductivity (EC) levels (control at 1.0 dS m −1 and salt at 8.0 dS m −1 ) in RBD design with four replications for six weeks. Significant reductions in leaf, shoot and root fresh and dry biomass productions, total leaf area, total root length, and total root volume of pepper plants were recorded under hydroponic salt stress. On the other hand, significant differences in salt tolerance among backcrossed peeper progenies and their respective parents existed. Particularly the progeny of BC3-3 was more tolerant characterized to salinity than the other progenies of third backcrossed and their respective parents. This was highly associated with vigorous root growth (root fresh and dry weight, total root length and volume) and photosynthetically active leaves (total leaf area, leaf chlorophyll index, chloride exclusion) under hydroponic salt stress. These traits could be useful characters to select and breed salt-tolerant pepper varieties for sustainable agriculture in the future.
Imprints of interfaces in thermoelectric materials

Abstract Contemporary thermoelectric literature is rife with material structure-related terminologies like interfaces and grain boundaries, signaling the significance of these structures. Interfaces decide the characteristics of electronic and thermal transport and mechanical properties of polycrystalline and nano thermoelectric (TE) materials. Understanding the relationship between grain boundaries/interphase boundaries and property connections in materials is a key component of material design with desired characteristics and performance. It is now widely recognized that the microstructure of materials is intimately connected to their bulk properties. Accordingly, microstructure control and interface manipulation have emerged as critical topics in the field of materials science and engineering, particularly in thermoelectrics. This paper narrates recent breakthroughs in high-performance TE material design from the standpoints of interface structure and grain boundary manipulation. First, it provides a glimpse of strategies for thermal conductivity reduction through nano and microstructure control, embedded nanoinclusions, grain size reduction, and all-scale hierarchical architectures. It then deliberates on electron and phonon transport decoupling via coherent interfaces, matrix/precipitate electronic band alignment, and charge carrier filtering effects. It proceeds to review the recent results on TE properties of materials prepared with aforementioned strategies emphasizing Bi2(Te,Se)3 and (Bi,Sb)2Te3, SnSe, SnTe, Cu2Se, skutterudides, PbTe-based compounds, GeTe, polymer TE composites, and other materials. At the end, possible strategies for further enhancing zT are addressed. Graphical Abstract
Data Center -Based, Service Oriented Architecture (SOA) in Cloud Computing

SOA and cloud computing are complementary activities; both will play important roles in IT planning for senior leadership teams for years to come. Cloud computing does not replace SOA or the use of distributed software components as an integration technology. SOA inspired componentization eff orts, where soft ware leverages other network based soft ware using standards-based interfaces. In this paper we discussed what it takes to build a cloud network, evolution from the managed service provider model to cloud computing roles as well as importance of collaboration, service-oriented architectures as an intermediary step and the basic approach to data center-based SOAs, and the role of open source software in data centers and where and how it is used in cloud architecture.
Comparison of two diagnostic methods through blood and urine sample analyses for the detection of ketosis in cattle

Background and Aim: Several Ecuadorian farms use human test strips (cheaper than veterinary strips) to diagnose bovine ketosis; however, their reliability is unknown. This study aimed to determine the confidence level of human strips for the detection of ketosis in bovines by comparing two diagnostic methods for ketosis: one used in bovines (gold standard) to analyze blood samples and the other used in humans to analyze urine samples. Materials and Methods: The study was conducted on an Ecuadorian farm using 50 animals, ten from each of five categories: heifers, 4 months pregnant (4MP), 15 days prepartum (15DPRE), 15 days postpartum (15DPOST), and 42 days postpartum (42DPOST). Blood samples were collected through coccygeal venipuncture and urine samples were collected during spontaneous urination. BHBCheck™ assay was used to measure b-hydroxybutyrate (BHB) in the blood, whereas Combur10Test® was used to measure acetoacetate (AcAc) in urine for the determination of ketosis. Results: BHB was detected in all animals. Based on a ketosis cutoff point of 0.8-1.2 mmol/L, 13 animals from the 15DPOST and 42DPOST categories had ketosis; AcAc was detected in the urine from nine animals originated from the two same categories. Metabolites, either BHB or AcAc, were not detected in heifers, 4MP, or 15DPRE individuals. Finally, the BHBCheck™ assay had better efficiency in detecting ketosis in animals (p<0.05) than the Combur10Test®. Conclusion: Combur10Test® urine strips reached 92% reliability for the detection of ketosis in dairy cattle, compared to BHBCheck™ assays.
Overview and Future Perspectives on Bone 3D Bioprinting

3D bioprinting is a prominent topic in the field of tissue engineering. The progress made in the last decade is remarkable, but the technology still shows many drawbacks and limitations due to the relatively short introduction. In this paper we summarize the major 3D bioprinting protocols such as material jetting, material extrusion, and vat polymerization, highlighting the pros and cons of each technology, then we analyze different biomaterials and various components of the bio-inks compatible with the available 3D bioprinters. The goal of this review is to examine the existing tools to produce bone scaffolds and highlight future developments in the field of Guided Bone Regeneration (GBR) inside the oral cavity.