Miracle-dz/UniFAR-FTUs huggingface dataset:
Approaches to rapid acting insulin intensification in patients with type 2 diabetes mellitus not achieving glycemic targets

Abstract Type 2 diabetes mellitus (T2DM) is a growing problem in the USA, affecting 30.3 million Americans, or 9.4% of the US population. Given that T2DM is a progressive disease, intensification of rapid acting insulin (RAI) to address hyperglycaemia is often required. The American Diabetes Association and the European Association for the Study of Diabetes recommend individualizing the treatment approach to glucose control, considering factors such as age, health behaviours, comorbidities and life expectancy. There are several validated treatment algorithms in the literature, which can be helpful for providing guidance on initiation of RAI while simultaneously considering patient preferences and clinical needs during treatment intensification. This paper provides expert recommendations on prandial insulin regimens and how to use treatment algorithms to promote better glucose control through best practice guidelines. To help patients reach HbA1c targets through treatment intensification, the FullSTEP, SimpleSTEP, ExtraSTEP and AUTONOMY algorithms are discussed in this paper. KEY MESSAGES Clinical inertia should be prevented with timely intensification of therapy when HbA1c levels are greater than 7% (or rising above a patient’s individual target) according to national guidelines. Increased personalization in the intensification of T2D treatment is necessary to improve HbA1c targets while addressing risk of hypoglycaemia, concern about weight gain, and overall health goals. Healthcare providers are encouraged to address glycaemic control with a variety of strategies, including prandial insulin, while developing evidence-based treatment plans on the basis of algorithms discussed in the literature.
Comparison of Three Random Forest Models of a Chiller System

The current building operation and maintenance is dependent on subjective decisions, e.g. building operator’s experience and knowledge, rather than employing a simulation model-assisted operation. It demands in-depth knowledge of building physics, systems and controls to develop the simulation model for optimal operation. Rather than using the first-principles based simulation tools, this paper presents a machine learning simulation model of a chiller in an office building. For this study, the BEMS data (a chiller’s electric energy, chiller supply water temperature, AHU return water temperature, AHU water flow rate, etc.) were collected from the existing office building (a total floor area: 21,577m). The authors used a Random Forest (RF) method, one of the machine learning techniques. Three RF models were developed and cross-compared in this study as follows: Model A developed with 12 variables from BEMS data, Model B developed with the 12 variables plus 18 new variables constructed by two arithmetic operators (a total of 20 variables), Model C with the 12 variables plus 6 new variables constructed based on physics-based equations (a total of 18 variables). The CVRMSE of the three models are 8.56%, 5.44% and 4.28%, respectively.
Physical and Chemical Characteristic Of Soil That Is Developing On Alangga And Meluhu Geological Formation In Various Land Use In Endanga Watershed, South East Sulawesi, Indonesia

The aim of this study is to analyze characteristic of developing soil on Alangga and Meluhu geological formation in various land use. This study was conducted in Endanga watershed which is a part of Konaweha watershed that is located in Landono and Mowila district, South Konawe region, South east Sulawesi province. The area of the watershed is ± 1353.67 ha, which is developing on geological formation Alangga and Meluhu that comprised of parent material conglomerate, sandstone, filit and quartz. The result shows that soil that was developing on parent material conglomerate, sandstone, filit and quartz has different physical and chemical characteristic. Soil texture in the study location is sandy loam, silty loam, sandy clay loam, value bulk density 0.97 g/cc to 1.29 g/cc, soil water content 3.4% to 50.9 %, porosity 43.4% to 58.7%.
Sorting machineries: how platelet-dense granules differ from α-granules

Platelets respond to vascular injury via surface receptor stimulation and signaling events to trigger aggregation, procoagulant activation, and granule secretion during hemostasis, thrombosis, and vascular remodeling. Platelets contain three major types of secretory granules including dense granules (or δ-granules, DGs), α-granules (AGs), and lysosomes. The contents of platelet granules are specific. Platelet DGs store polyphosphate and small molecules such as ADP, ATP, Ca2+, and serotonin, while AGs package most of the proteins that platelets release. The platelet DGs and AGs are regarded as being budded from the endosomes and the trans-Golgi network (TGN), respectively, and then matured from multivesicular bodies (MVBs). However, the sorting machineries between DGs and AGs are different. Inherited platelet disorders are associated with deficiency of DGs and AGs, leading to bleeding diathesis in patients with Hermansky–Pudlak syndrome (HPS), gray platelet syndrome (GPS), and arthrogryposis, renal dysfunction, and cholestasis syndrome (ARC). Here, we reviewed the current understanding about how DGs differ from AGs in structure, biogenesis, and function. In particular, we focus on the sorting machineries that are involved in the formation of these two types of granules to provide insights into their diverse biological functions.
A Parametric Analysis and Classification of Quests in MMORPGs

Massively multiplayer online role-playing games (MMORPG) are a particular sub-genre of massively multiplayer online games (MMOG) whose commercial importance has experienced a growth spurt in the last five years marked by commercially successful games such as World of Warcraft. A characteristic of the genre is a focus on character progression and openended narratives by means of quests, which represent tasks assigned to the players in exchange for in-game rewards. Progression mechanisms typically involve static requirements defined by the game designers, in such a way that players of different skill levels performing a set of quests always face the same challenge and obtain the same rewards. As a consequence, speed of progression through the game is completely disassociated from player experience and skills. This paper proposes a comprehensive quest classification model, as well as the set of difficulty parameters associated to each quest class, by the exhaustive analysis of 480 quests. This allows for the creation of quest variants specifically tailored to the needs of each player by the game designers, and constitutes the first step towards a dynamic difficulty adjustment (DDA) implementation.
A Proactive Travel Time Based Ramp Metering Algorithm for an Isolated Ramp

This paper focuses on the design of a proactive ramp metering control on an isolated ramp. The developed approach exploits the use of vehicle probe travel time data as the main input parameters to the ramp metering control algorithm. The problem is formulated with the objective of minimizing total system vehicular travel time and includes: 1) travel time on the freeway, upstream and downstream of the ramp; and, 2) the wait time on the ramp. The Cell Transmission Model (CTM) and shockwave analysis are used to predict the travel time on the freeway. Delays on the ramp are obtained based on deterministic queuing theory. The developed approach is tested using Quadstone Paramics’ microsimulation model on an isolated ramp on Highway 2 in Calgary, Canada. The developed algorithm is analyzed under various traffic conditions on the freeway and ramp. In addition, a sensitivity analysis is conducted to examine the performance of the developed algorithm for various values as the ramp input parameters: percentages of penetration of probe data and estimation step intervals. The results of the analysis are promising, showing the effectiveness of developing ramp metering control algorithms based on travel time data from vehicle probes.
Ka-Band CMOS 360° Reflective-Type Phase Shifter with ±0.2 dB Insertion Loss Variation Using Triple-Resonating Load and Dual-Voltage Control Techniques

This paper demonstrates the design of a Ka-band 360° reflective-type phase shifter (RTPS). Triple-resonating load technique is used to reach broadband full 360° phase-shift range and achieve low insertion loss variation. With dual-voltage control technique adopted, insertion loss variation is further reduced. Implemented in 65nm CMOS technology, the proposed RTPS achieves 379° phase-shift range at 29 GHz with only one control voltage. With dual-voltage control, a measured phase-shift range of 360° with 8.3 ± 0.2 dB insertion loss is achieved at 29 GHz. It also ensures 360° phase-shift range and 8–9 dB insertion loss (i.e., <1 dB variation) across 27.8–31.2 GHz. The corresponding return loss across frequencies are better than 20 dB.
Gesture-based target acquisition in virtual and augmented reality

Abstract Background Gesture is a basic interaction channel that is frequently used by humans to communicate in daily life. In this paper, we explore to use gesture-based approaches for target acquisition in virtual and augmented reality. A typical process of gesture-based target acquisition is: when a user intends to acquire a target, she performs a gesture with her hands, head or other parts of the body, the computer senses and recognizes the gesture and infers the most possible target. Methods We build mental model and behavior model of the user to study two key parts of the interaction process. Mental model describes how user thinks up a gesture for acquiring a target, and can be the intuitive mapping between gestures and targets. Behavior model describes how user moves the body parts to perform the gestures, and the relationship between the gesture that user intends to perform and signals that computer senses. Results In this paper, we present and discuss three pieces of research that focus on the mental model and behavior model of gesture-based target acquisition in VR and AR. Conclusions We show that leveraging these two models, interaction experience and performance can be improved in VR and AR environments.
Parameters Affecting the Back Flashover across the Overhead Transmission Line Insulator Caused by Lightning

This paper describes analysis study on some factors, which affecting the back flashover across the insulator in a transmission system. Parameters of this study include the modeling of transmission line tower, the modeling of tower footing ground system, magnitude of lightning stroke, front and tail times of lightning stroke impulse, and striking distance. All components of the system, which is under study, are simulated by using ATP program.
Human Navigational Performance in a Complex Network with Progressive Disruptions

The current paper is an investigation towards understanding the navigational performance of humans on a network when the "landmark" nodes are blocked. We observe that humans learn to cope up, despite the continued introduction of blockages in the network. The experiment proposed involves the task of navigating on a word network based on a puzzle called the wordmorph. We introduce blockages in the network and report an incremental improvement in performance with respect to time. We explain this phenomenon by analyzing the evolution of the knowledge in the human participants of the underlying network as more and more landmarks are removed. We hypothesize that humans learn the bare essentials to navigate unless we introduce blockages in the network which would whence enforce upon them the need to explore newer ways of navigating. We draw a parallel to human problem solving and postulate that obstacles are catalysts for humans to innovate techniques to solve a restricted variant of a familiar problem.
The retreat chronology of the Laurentide Ice Sheet during the last 10 , 000 years and implications for deglacial sea-level rise

This paper presents a comprehensive review and synthesis of ice streams in the Laurentide Ice Sheet (LIS) based on a new mapping inventory that includes previously hypothesised ice streams and includes a concerted effort to search for others from across the entire ice sheet bed. The inventory includes 117 ice streams, which have been identified based on a variety of evidence including their bedform imprint, largescale geomorphology/topography, till properties, and ice rafted debris in ocean sediment records. Despite uncertainty in identifying ice streams in hard bedrock areas, it is unlikely that any major ice streams have been missed. During the Last Glacial Maximum, Laurentide ice streams formed a drainage pattern that bears close resemblance to the present day velocity patterns in modern ice sheets. Large ice streams had extensive onset zones and were fed by multiple tributaries and, where ice drained through regions of high relief, the spacing of ice streams shows a degree of spatial self-organisation which has hitherto not been recognised. Topography exerted a primary control on the location of ice streams, but there were large areas along the western and southern margin of the ice sheet where the bed was composed of weaker sedimentary bedrock, and where networks of ice streams switched direction repeatedly and probably over short time scales. As the ice sheet retreated onto its low relief interior, several ice streams show no correspondence with topography or underlying geology, perhaps facilitated by localised build-up of pressurised subglacial meltwater. They differed from most other ice stream tracks in having much lower length-to-width ratios and have no modern analogues. There have been very few attempts to date the initiation and cessation of ice streams, but it is clear that ice streams switched on and off during deglaciation, rather than maintaining the same trajectory as the ice margin retreated. We provide a first order estimate of changes in ice stream activity during deglaciation and show that around 30% of the margin was drained by ice streams at the LGM (similar to that for present day Antarctic ice sheets), but this decreases to 15% and 12% at 12 cal ka BP and 10 cal ka BP, respectively. The extent to which these changes in the ice stream drainage network represent a simple and predictable readjustment to a changing mass balance driven by climate, or internal ice dynamical feedbacks unrelated to climate (or both) is largely unknown and represents a key area for future work to address.  Previous article in issue  Next article in issue
INVITED REVIEW SERIES: MOLECULAR TECHNIQUES FOR RESPIRATORY DISEASES

The proteome is the study of the protein content of a definable component of an organism in biology. However, the tissue-specific expression of proteins and the varied post-translational modifications, splice variants and protein–protein complexes that may form, make the study of protein a challenging yet vital tool in answering many of the unanswered questions in medicine and biology to date. Indeed, the spatial, temporal and functional composition of proteins in the human body has proven difficult to elucidate for many years. Given the effect of microRNA and epigenetic regulation on silencing and enhancing gene transcription, the study of protein arguably provides more accurate information on homeostasis and perturbation in health and disease. There have been significant advances in the field of proteomics in recent years, with new technologies and platforms available to the research community. In this review, we briefly discuss some of these new technologies and developments in the context of respiratory disease. We also discuss the types of data science approaches to analyses and interpretation of the large volumes of data generated in proteomic studies. We discuss the application of these technologies with regard to respiratory disease and highlight the potential for proteomics in generating major advances in the understanding of respiratory pathophysiology into the future.
Unleashing Fine-Grained Parallelism on Embedded Many-Core Accelerators with Lightweight OpenMP Tasking

In recent years, programmable many-core accelerators (PMCAs) have been introduced in embedded systems to satisfy stringent performance/Watt requirements. This has increased the urge for programming models capable of effectively leveraging hundreds to thousands of processors. Task-based parallelism has the potential to provide such capabilities, offering high-level abstractions to outline abundant and irregular parallelism in embedded applications. However, efficiently supporting this programming paradigm on embedded PMCAs is challenging, due to the large time and space overheads it introduces. In this paper we describe a lightweight OpenMP tasking runtime environment (RTE) design for a state-of-the-art embedded PMCA, the Kalray MPPA 256. We provide an exhaustive characterization of the costs of our RTE, considering both synthetic workload and real programs, and we compare to several other tasking RTEs. Experimental results confirm that our solution achieves near-ideal parallelization speedups for tasks as small as 5K cycles, and an average speedup of 12<inline-formula><tex-math notation="LaTeX">$\times$</tex-math><alternatives> <inline-graphic xlink:href="tagliavini-ieq1-2814602.gif"/></alternatives></inline-formula> for real benchmarks, which is <inline-formula><tex-math notation="LaTeX">$\approx 60\%$</tex-math><alternatives> <inline-graphic xlink:href="tagliavini-ieq2-2814602.gif"/></alternatives></inline-formula> higher than what we observe with the original Kalray OpenMP implementation.
An Optimal Capacity-Delay Tradeoff with Appropriate Contention Count based on Correlation of Node Mobility in MANET

In MANET, different challenges have been addressed for providing a better performance regarding higher throughput, less delay and reduced transmission overhead. Due to the heterogeneous degrees of correlated mobility of nodes, there was a considerable effect in capacity delay-tradeoff in these networks. Therefore, a medium correlation of node mobility was maintained for optimizing capacity-delay tradeoff. However, this optimal capacity-delay tradeoff was not sufficient for providing better Quality-ofService (QoS) in MANET. As a result, reliability and link stability are to be selected for providing high bandwidth utilization, high throughput and stable jitter. Hence in this article, a QoS-aware routing metric is incorporated with the correlated mobility. In this scheme, the Link Stability Factor(LSF) is estimated by considering the received signal strength, pertinent contention count and hop count. Based on the estimated LSF, stable link is determined. After that, the node with the highest LSF is elected as a reliable forwarding node. Thus, the proposed scheme improves QoS performance. Finally, the experimental results are demonstrated that the proposed scheme outperforms than the existing method in connection to routing overhead, ratio on packet delivery and end-to-end delay.
A human body powered sensory glove system based on multisource energy harvester

In this work we present and evaluate a multi-source power management system, based on human body energy harvesting, to extend the battery lasting of an electronic sensory glove, used to measure flexion/extension, abduction/adduction movements of fingers of the hand. The system exploits heat of the human forearm and pressure impressed by the foot heel during walking, so to gather additional energy. The aim is to allow hours of energy-autonomy for the user working with the sensory glove. Such a glove is equipped with a number of flex sensors which furnish data from finger movements, acquired and pre-processed by a microcontroller, and wireless sent to a Personal Computer for analysis, visualization and storage purposes. The multi-source harvester is based on vibrational and thermic sources. Prototype discrete element boards were designed and tested for the microelectronics integration. Measurement results demonstrate how the overall system extends the battery lasting time up to 20%.
Performance Improvement of Vision Based Fire Detection System

In this paper an optimized fire detection system using image processing is proposed. This system is based on combination of various methods used for fire detection using image processing. This system can also be adjusted according to different sensitive area requirement by applying different combination of fire detecting techniques. The proposed system gives optimized way to detect the fire in terms of fewer false alarms by giving the accurate result of fire occurrence. Conventional fire detection systems use physical sensors to detect fire. Chemical properties of particles in the air are acquired by sensors and are used by conventional fire detection systems to raise an alarm. However, this can also cause false alarms. In order to reduce false alarms of conventional fire detection systems, we proposed vision-based fire detection system. The proposed fire detection system consists of main parts: fire edge detection, colour detection, motion detection, gray-cycle pixel detection of smoke and area spread. Index Terms – Fire Detection, Image Processing, Colour Detection, Motion Detection, Edge Detection, Grey Cycle Detection.
Prominent Non-Memory Deficits in Alzheimer's Disease Are Associated with Faster Disease Progression.

BACKGROUND Alzheimer's disease (AD) is a heterogeneous disorder. OBJECTIVE To investigate whether cognitive AD subtypes are associated with different rates of disease progression. METHODS We included 1,066 probable AD patients from the Amsterdam Dementia Cohort (n = 290), Alzheimer's Disease Neuroimaging Initiative (n = 268), Dementia Competence Network (n = 226), and University of California, San Francisco (n = 282) with available follow-up data. Patients were previously clustered into two subtypes based on their neuropsychological test results: one with most prominent memory impairment (n = 663) and one with most prominent non-memory impairment (n = 403). We examined associations between cognitive subtype and disease progression, as measured with repeated Mini-Mental State Examination (MMSE) and Clinical Dementia Rating scale sum of boxes (CDR sob), using linear mixed models. Furthermore, we investigated mortality risk associated with subtypes using Cox proportional hazard analyses. RESULTS Patients were 71±9 years old; 541 (51%) were female. At baseline, pooled non-memory patients had worse MMSE scores (23.1±0.1) and slightly worse CDR sob (4.4±0.1) than memory patients (MMSE 24.0±0.1; p < 0.001; CDR sob 4.1±0.1; p < 0.001). During follow-up, pooled non-memory patients showed steeper annual decline in MMSE (-2.8±0.1) and steeper annual increase in CDR sob (1.8±0.1) than memory patients (MMSE - 1.9±0.1; pinteraction<0.001; CDR sob 1.3±0.1; pinteraction<0.001). Furthermore, the non-memory subtype was associated with an increased risk of mortality compared with the memory subtype at trend level (HR = 1.36, CI = 1.00-1.85, p = 0.05). CONCLUSIONS AD patients with most prominently non-memory impairment show faster disease progression and higher risk of mortality than patients with most prominently memory impairment.