Miracle-dz/UniFAR-FTUs huggingface dataset:
Derivation and validation of a machine learning risk score using biomarker and electronic patient data to predict rapid progression of diabetic kidney disease

Importance: Diabetic kidney disease (DKD) is the leading cause of kidney failure in the United States and predicting progression is necessary for improving outcomes. Objective: To develop and validate a machine-learned, prognostic risk score (KidneyIntelXTM) combining data from electronic health records (EHR) and circulating biomarkers to predict DKD progression. Design: Observational cohort study Setting: Two EHR linked biobanks: Mount Sinai BioMe Biobank and the Penn Medicine Biobank. Participants: Patients with prevalent DKD (G3a-G3b with all grades of albuminuria (A1-A3) and G1 & G2 with A2-A3 level albuminuria) and banked plasma. Main outcomes and measures: Plasma biomarkers soluble tumor necrosis factor 1/2 (sTNFR1, sTNFR2) and kidney injury molecule-1 (KIM-1) were measured at baseline. Patients were divided into derivation [60%] and validation sets [40%]. A composite primary end point of rapid kidney function decline (RKFD) (estimated glomerular filtration rate (eGFR) decline of [≥]5 ml/min/1.73m2/year), [≥]40% sustained decline, or kidney failure within 5-years. A machine learning model (random forest) was trained and performance assessed using standard metrics. Results: In 1146 patients with DKD the median age was 63, 51% were female, median baseline eGFR was 54 ml/min/1.73 m2, urine albumin to creatinine ratio (uACR) was 61 mg/g, and follow-up was 4.3 years. 241 patients (21%) experienced RKFD. On 10-fold cross validation in the derivation set (n=686), the risk model had an area under the curve (AUC) of 0.77 (95% CI 0.74-0.79). In validation (n=460), the AUC was 0.77 (95% CI 0.76-0.79). By comparison, the AUC for an optimized clinical model was 0.62 (95% CI 0.61-0.63) in derivation and 0.61 (95% CI 0.60-0.63) in validation. Using cutoffs from derivation, KidneyIntelX stratified 47%, 37% and 16% of validation cohort into low-, intermediate- and high-risk groups, with a positive predictive value (PPV) of 62% (vs. 41% for KDIGO) in the high-risk group and a negative predictive value (NPV) of 91% in the low-risk group. The net reclassification index for events into high-risk group was 41% (p<0.05). Conclusions and Relevance: A machine learned model combining plasma biomarkers and EHR data improved prediction of adverse kidney events within 5 years over KDIGO and standard clinical models in patients with early DKD.
Progress towards the Ending Preventable Maternal Mortality (EPMM) target for Bangladesh: The role of female education

Educational attainment among women is a well-recognized predictor for maternal mortality. Data from nationally representative surveys and the United Nations are used in the analysis for estimating maternal mortality due to improved education status up to 2030. Analysis of data from 2001 and 2010 Bangladesh Maternal Mortality Survey shows that MMR varies considerably by education level. The study shows that during 2011-2030, 15% maternal deaths will be averted due to fertility change (i.e. fewer births) and 24% of the maternal deaths can be averted only by improving the female education levels. However, in order to achieve the Ending Preventable Maternal Mortality (EPMM) target of 59 maternal deaths per 100,000 live births by 2030 for Bangladesh, a further 64% reduction will be required. Factors outside the health sector, like female education, will continue to have an impact maternal mortality in Bangladesh. However, reaching the EPMM target for Bangladesh by 2030 will also require significant investments in maternal health programs, in particular those to increase access to and quality of services.
Development and structure of microbial biofilms in river water studied by confocal laser scanning microscopy

The development of stream biofilms was studied using a rotating annular biofilm reactor system for cultivation and confocal laser scanning microscopy for structural examination. Biofilms were generated by feeding the reactor with raw river water as inoculum and a sole nutrient source. The biofilm developed during 56 days from microcolonies via a thin patchy film into a ridged structure. The ridges were oriented parallel to the direction of flow. The parallel ridges varied from a few microns up to 500 μm thick and consisted of cellular and non-cellular material. The architecture of the film was in contrast to previous views of a homogeneous biofilm structure and more recent biofilm models with channels and inverted biomass distribution. The difference may be attributed to the presence and co-adsorption of humic and detrital material in natural lotic systems. This material building the ridges supplied an increased surface area for colonization and may serve as an additional source of nutrients. The biofilms on the removable slides showed a thickness gradient across the width and the length of the slides which may be caused by the flow pattern of the water inside the reactor. By using a live/dead fluorescent probe the population heterogeneity of the biofilm was demonstrated in space and time. In addition, the dominance of certain bacteria and their extracellular polymeric products was examined using lectin binding analyses. The rotating annular biofilm reactor may be a useful tool for morphological studies of complex microbial films, particularly those developing under turbulent flow regimes which are typical for aqueous environmental ecosystems.
The Mini Linguistic State Examination (MLSE): a brief but accurate assessment tool for classifying Primary Progressive Aphasias

Background: This paper introduces a new clinical test, the Mini Linguistic State Examination (MLSE), as a short assessment for screening and classification of the different manifestations of primary progressive aphasia (PPA). Differentiation and monitoring of PPA variants are vital for management, planning and development of new treatments. The MLSE is designed to improve the uniformity of testing, screening for recruitment to clinical trials, and consistency of research results. It is a brief but effective test which can be adapted to the worlds major languages. Methods: Fifty-four patients and 30 age-, sex- and education-matched controls completed testing with the MLSE and components of the Boston Diagnostic Aphasia Examination in addition to their standard clinical diagnostic assessment. The MLSE includes five domains (motor speech, phonology, semantics, syntax and working memory) that were compared across groups. A random forest classification was used to learn the relationship between these five domains and assess the power of the diagnostic accuracy for predicting PPA subtypes. The final machine learning model was used to create a decision tree to guide the optimal manual classification of patients. Results: On average, the test took less than 20 minutes to administer. Significant group differences were found across all five domains, in terms of the distributions of error-types. These differences mirror the well-known language profiles for the three main PPA variants, which typically require an extended neuropsychology and speech pathology assessment. The random forest prediction model had an overall classification accuracy of 96% (92% for logopenic variant PPA, 93% for semantic variant PPA and 98% for non-fluent variant PPA). The derived decision tree for manual classification produced correct classification of 91% of participants whose data were not included in the training set. Conclusions: The MLSE is a new short cognitive test, with a scoring system that is easy to learn and apply. It is accurate for classifying PPA syndromes, and has potential to screen and monitor language deficits that occur in other focal and neurodegenerative brain disorders associated with language impairment. With increasing importance of language assessment in clinical research, the MLSEs linguistic assessment tool enables the essential profiling of language deficits in a wide clinical community.
ADAPTIVE ECG FILTERING AND QRS DETECTION USING ORTHOGONAL WAVELET TRANSFORM

Biomedical signals like heart wave commonly change their statistical properties over time, tending to be nonstationary. For analysing this kind of signal wavelet transforms are a powerful tool. In this paper we utilize orthogonal wavelets to filter and analyse ECG signals. First, we use compactly supported wavelets associated to the statistical Stein’s Unbiased Risk Estimator (SURE) in order to obtain an adaptive thresholding strategy to filter ECG signals. Second, we analyse the filtered signals by using the Haar wavelet transform in order to detect the positions of the occurrence of the QRS complex during the period of analysis. As results we obtain a more efficient filter, since the threshold value depends on the magnitude of wavelet coefficients in each level, and also a lightweight QRS detection algorithm.
Mutational Analysis of Target Enzyme Recognition of the β-Trefoil Fold Barley α-Amylase/Subtilisin Inhibitor*

The barley α-amylase/subtilisin inhibitor (BASI) inhibits α-amylase 2 (AMY2) with subnanomolar affinity. The contribution of selected side chains of BASI to this high affinity is discerned in this study, and binding to other targets is investigated. Seven BASI residues along the AMY2-BASI interface and four residues in the putative protease-binding loop on the opposite side of the inhibitor were mutated. A total of 15 variants were compared with the wild type by monitoring the α-amylase and protease inhibitory activities using Blue Starch and azoalbumin, respectively, and the kinetics of binding to target enzymes by surface plasmon resonance. Generally, the mutations had little effect on kon, whereas the koff values were increased up to 67-fold. The effects on the inhibitory activity, however, were far more pronounced, and the Ki values of some mutants on the AMY2-binding side increased 2–3 orders of magnitude, whereas mutations on the other side of the inhibitor had virtually no effect. The mutants K140L, D150N, and E168T lost inhibitory activity, revealing the pivotal role of charge interactions for BASI activity on AMY2. A fully hydrated Ca2+ at the AMY2-BASI interface mediates contacts to the catalytic residues of AMY2. Mutations involving residues contacting the solvent ligands of this Ca2+ had weaker affinity for AMY2 and reduced sensitivity to the Ca2+ modulation of the affinity. These results suggest that the Ca2+ and its solvation sphere are integral components of the AMY2-BASI complex, thus illuminating a novel mode of inhibition and a novel role for calcium in relation to glycoside hydrolases.
Pressurized Fluid Processing: From by-products to high value-added products

Canada generates annually million tonnes of by-products, such as potato cull, lupin hull, canola straw among others. These by products have valuable components, such as starch, cellulose, sugars and phenolics, which can be used as sweeteners, stabilizers, bioethanol, and in packaging applications. Using two of these by-products, our laboratory produced bioactive starch films, phenolics, and nanocellulose with subcritical water (SCW) and pressurized fluid technology. All experiments were performed using a subcritical fluid reaction system. The effects of temperature and pressure were studied for all reactions. Bioactive films produced were characterized by mechanical, physico-chemical, optical and functional properties. Total phenolics were analyzed by spectrophotometer methods, while individual hemicellulosic sugars were analyzed by HPLC. Other characterizations include morphology and particle size. For the bioactive films, 100% of elongation was obtained. Bioactive films also showed high antioxidant activity. Using pressurized fluids, temperature was the most important process parameter for straw hydrolysis due to the break of ether and ester interactions between lignin and hemicellulose. At optimized conditions, hemicellulosic sugars were removed, providing a rich cellulose residue, which was successfully converted to nanocellulose using pressurized fluid followed by ultrasonication. Therefore, SCW is a suitable technology to produce bioactive starch films, and other high value-added compounds like nanocellulose.
CLAN: Continuous Learning using Asynchronous Neuroevolution on Commodity Edge Devices

Recent advancements in machine learning algorithms, especially the development of Deep Neural Networks (DNNs) have transformed the landscape of Artificial Intelligence (AI). With every passing day, deep learning based methods are applied to solve new problems with exceptional results. The portal to the real world is the edge. The true impact of AI can only be fully realized if we can have AI agents continuously interacting with the real world and solving everyday problems. Unfortunately, high compute and memory requirements of DNNs acts a huge barrier towards this vision. Today we circumvent this problem by deploying special purpose inference hardware on the edge while procuring trained models from the cloud. This approach, however, relies on constant interaction with the cloud for transmitting all the data, training on massive GPU clusters, and downloading updated models. This is challenging for bandwidth, privacy, and constant connectivity concerns that autonomous agents may exhibit. In this paper we evaluate techniques for enabling adaptive intelligence on edge devices with zero interaction with any high-end cloud/server. We build a prototype distributed system of Raspberry Pis communicating via WiFi running NeuroEvolutionary (NE) learning and inference. We evaluate the performance of such a collaborative system and detail the compute/communication characteristics of different arrangements of the system that trade-off parallelism versus communication. Using insights from our analysis, we also propose algorithmic modifications to reduce communication by up to 3.6x during the learning phase to enhance scalability even further and match performance of higher end computing devices at scale. We believe that these insights will enable algorithm-hardware co-design efforts for enabling continuous learning on the edge.
Synthesis of Core-shell structured Zinc Oxide- Polymethylmethacrylate (PMMA) Films through Wet Chemical Method

Zinc Oxide-Polymethylmethacrylate (ZnO-PMMA) core shell structured nanoparticles with inorganic core and the polymer shell were prepared successfully. ZnO has been selected in the present study for preparing the core shell nanoparticles in PMMA matrix for obtaining the UV-protection and high degree of transparency of the synthesized films in visible region. The outer surface of ZnO nanoparticles was initially modified by Cetyl Trimethylammonium Bromide (CTAB) to inhibit the agglomeration of ZnO nanoparticles and promote their compatibility with PMMA. The ZnO-PMMA nanoparticles films, prepared by Spin Coating Technique, were then characterized by X-ray Diffraction (XRD), High Resolution Transmission Electron Microscopy (HRTEM), Fourier Transform Infrared Spectroscopy (FTIR) and UV–Visible Absorption Spectroscopy to study their structural, micro-structural and optical properties. The synthesized films demonstrate UV–Absorbing capacity and good amount of optical transparency in the visible-wavelength region.
Reducing Kernel Queuing Delays with TCP Window Space Events

The combination of TCP auto-tuning and asynchronous I/O event notiﬁcations (e.g., epoll ) allows the Linux kernel to generally sustain high-volume TCP connections—even for connections with high bandwidth-delay products (high link bandwidth and/or high path latency). However, bufferbloat can quickly become an issue when multiple such connections are in use. In particular, high outbound kernel queuing delays have been observed in the Tor anonymity network, a large distributed system whose relays often manage thousands of sockets—many of which are simultaneously-active, high-volume TCP connections. In this work, we propose a new notiﬁcation event that triggers when TCP is ready to send data on a socket while seeking to better understand how it can help applications to better manage network I/O and improve performance. The new event supplements and extends the current write event that triggers when a socket buffer has free space , and the difference in semantics allows more precise control over queuing to the application. We describe the problem, detail a proposal for extending epoll to support the new semantics (including a code patch), and show the effect that such a change could have on performance through a small scale simulation.
Centralized Scheduling of Distributed Energy Resources in an Isolated Micro grid

Micro grid comprises of various Distributed Energy Resources, Battery Energy Storage System (BESS) and various loads that can be connected to a grid or can be operated in an isolated mode. In this paper, micro grid comprises of a Diesel Generator set, wind turbine generator, Battery Energy Storage System (BESS) to feed a critical load in an isolated location. The intermittent energy from wind power is stored in BESS and a Centralized micro controller program is used to schedule the operation of Diesel Generator and BESS to provide an uninterrupted power supply to the critical load. The communication link between the microcontroller and Distribution Energy Resources will be a satellite link (GPRS/3G/4G/5G) or optical fibre cable. The main objective of this work is to reduce the usage of diesel generator output and utilizing the renewable energy in place of it to its maximum capacity. Meanwhile by proper scheduling, continuous working of BESS is ensured within its SOC limits. In this work, MATLAB simulation is used to simulate the load sharing among Diesel Generator and BESS. A hardware prototype is designed in proteus software and the hardware prototype is fabricated to verify the simulation results.
RECOVERING FROM THE NIGHTMARE OF RANSOMWARE – HOW SAVVY USERS GET HIT WITH VIRUSES AND MALWARE: A PERSONAL CASE STUDY

The purpose of this paper is to describe the ways that savvy computer users unknowingly install malware on their computers and thus infecting and causing damage to their files and computers. In particular, it focuses on one type of malware that is being repeatedly downloaded and installed by users from different levels of expertise in terms of their use of computers. The name of this malware is ransomware. This type of malware is dangerous and is creating havoc in the life of many users. These users include one of the authors of this paper that unknowingly downloaded and installed this malware. It damaged the contents of his family computer that is currently still undergoing reconstruction. The experience of this particular case along with relevant description of the malware and related literature is included in this study.
Effects of controlling temperature and light duration on seed production in tilapia, Oreochromis spilurus (Gunther)

An experiment was conducted to compare the seed production of tilapia, Oreochromis spilurus (Gunther), under ambient water temperature and photoperiod, and under controlled water temperature (29.0 ± 2.0 °C), and photoperiods of 13 and 14 h day−1. Male and female breeders with average weights of 155.4 and 78.7 g, respectively, were stocked in nine 1.04 X 1.04 X 0.40 m (L X W X H) fibreglass tanks. Each tank was stocked with two males and six females. Seed collection was carried out biweekly for 300 days. The results showed that the seed kg−1 female day−1, seed m−2day−1, total seed production per tank and spawning rates of females were highest during the 14 h day−1 photoperiod (112.4, 77.4, 24 724 and 42.1%, respectively), followed by ambient spawning conditions (104.0, 57.9, 18 356 and 36.6%, respectively), and lowest during the 13 h day−1 photoperiod (49.5, 36.5, 12 021 and 25.7%, respectively). Under ambient spawning conditions, peak spawning occurred in May. Monthly seed production was affected by changes in temperature and light duration. In both controlled photoperiods, the peak of seed production was observed during the first month after stocking. In all treatments, spawning declined gradually after the peak, which can be attributed to exhaustion of the breeders. The findings of this study indicate that seed production of O. spilurus in Kuwait can be extended beyond the restricted spawning season of 6-7 months by maintaining water temperature at 29.0 ± 2.0 °C and photoperiod at 14 h day−1.
A contribution to the mammalogy of the Sinai Peninsula

Une enquete a ete entreprise sur le terrain pour recueillir des donnees sur la repartition actuelle des mammiferes terrestres de la peninsule du Sinai. Ce travail a couvert les principaux biotopes et de nombreuses localites. Diverses methodes de capture, en plus de l'observation directe des animaux, de leurs traces et d'autres indices de leur presence, ainsi que les indications donnees par les Bedouins, ont permis de collecter des indications sur la presence de 21 especes de mammiferes; en particulier Hystrix indica et Vormela peregusna ainsi que Vulpes v. arabica sont repertories pour la premiere fois.
Developmental Strategies in Diagnosing Obstructive Sleep Apnea

A key mission in medical science is diagnosing a disease due to its criticality and accuracy in examining whether a patient is suffering from particular disease or not. Then, the most appropriate side of treatment can be decided. Obstructive Sleep Apnea (OSA) syndrome is the most widespread sleep disorder characterized by chronic episodes of reduction in the airflow or stoppage in airflow during sleep, being caused by blockage of upper airway. The intention of this review is to analyze already existing algorithms for detecting apnea all the way through usage of different sensors that have not been implemented on hardware. This study offers an exhaustive literature research value from 2003 to 2019 and setting a roadmap for bio-engineers and medical doctors thereby reducing research period and improving medical service efficiency concerning obstructive sleep apnea diagnosis.
Koala birth seasonality and sex ratios across multiple sites in Queensland, Australia

Abstract Establishing accurate demographic information for free-ranging populations of animals is difficult without knowledge of individual chronological age. We estimated the birth dates of 743 koala (Phascolarctos cinereus) joeys at 3 sites in Queensland, Australia, using body mass obtained from a reference population with known birth dates. From these age estimates we compared the annual distribution of births across calendar months. At all 3 locations about 60% of births occurred between December and March. The annual pattern of births was identical for males and females within locations, but overall annual patterns of births differed between the southern and northern sites. We conclude that koalas can bear offspring in every month of the year, but breed seasonally across Australia, and that a sex bias in the timing of births is absent from most regions.
Variation in search and predatory attack strategies of shark mackerel Grammatorcynus bicarinatus

I observed shark mackerel demonstrating multiple search and attack strategies. Strategies were categorized as three distinct types: (1) a linear search by single or groups of fish along reef features; (2) ambush from a stationary position on the seafloor; and (3) ambush from resting schools of co-occurring predators. Together these strategies were consistent with both information-sharing and producer–scrounger models of group foraging and indicate significant flexibility in individual fish foraging behaviour based on proximate conditions.