Miracle-dz/UniFAR-FTUs huggingface dataset:
Using YOLO based deep learning network for real time detection and localization of lung nodules from low dose CT scans

Lung cancer is the leading cause of cancer related deaths in the world. The survival rate can be improved if the presence of lung nodules are detected early. This has also led to more focus being given to computer aided detection (CAD) and diagnosis of lung nodules. The arbitrariness of shape, size and texture of lung nodules is a challenge to be faced when developing these detection systems. In the proposed work we use convolutional neural networks to learn the features for nodule detection, replacing the traditional method of handcrafting features like geometric shape or texture. Our network uses the DetectNet architecture based on YOLO (You Only Look Once) to detect the nodules in CT scans of lung. In this architecture, object detection is treated as a regression problem with a single convolutional network simultaneously predicting multiple bounding boxes and class probabilities for those boxes. By performing training using chest CT scans from Lung Image Database Consortium (LIDC), NVIDIA DIGITS and Caffe deep learning framework, we show that nodule detection using this single neural network can result in reasonably low false positive rates with high sensitivity and precision.
Structured Reporting in Neuroradiology: Intracranial Tumors

Purpose The aim of this pilot study was to assess the clinical feasibility, diagnostic yield, advantages, and disadvantages of structured reporting for routine MRI-reading in patients with primary diagnosis of intracranial tumors as compared to traditional neuroradiological free text reporting. Methods A structured MRI reporting template was developed covering pathological, anatomical, and functional aspects in an itemized fashion. Retrospectively, 60 consecutive patients with first diagnosis of an intracranial tumor were selected from the radiology information system/PACS system. Structured reporting was performed by a senior neuroradiologist, blinded to clinical and radiological data. Reporting times were measured per patient. The diagnostic content was compared to free text reporting which was independently performed on the same MRI exams by two other neuroradiologists. The comparisons were categorized per item as: “congruent,” “partially congruent,” “incongruent,” or “not mentioned in free-style report. ” Results Tumor-related items: congruent findings were found for all items (17/17) with congruence rates ranging between 98 and 39% per item. Four items achieved congruence rates ≥90%, 5 items >80%, and 9 items ≥70%. Partially congruent findings were found for all items in up to 50% per item. Incongruent findings were present in 7/17 items in up to 5% per item. Free text reports did not mention 12 of 17 items (range 7–43% per item). Non-tumor-related items, including brain atrophy, microangiopathy, vascular pathologies, and various extracranial pathologies, which were not mentioned in free-text reports between 18 and 85% per item. Mean reporting time for structured reporting was 7:49 min (3:12–17:06 min). Conclusion First results showed that expert structured reporting ensured reliable detection of all relevant brain pathologies along with reproducible documentation of all predefined diagnostic items, which was not always the case for free text reporting. A mean reporting time of 8 min per patient seems clinically feasible.
Reducing read latency of phase change memory via early read and Turbo Read

Phase Change Memory (PCM) is an emerging memory technology that can enable scalable high-density main memory systems. Unfortunately, PCM has higher read latency than DRAM, resulting in lower system performance. This paper investigates architectural techniques to improve the read latency of PCM. We observe that there is a wide distribution in cell resistance in both the SET state and the RESET state, and that the read latency of PCM is designed conservatively to handle the worst case cell. If PCM sensing can be tuned to exploit the variability in cell resistance, then we can get reduced read latency. We propose two schemes to enable better-than-worst-case read latency for PCM systems. Our first proposal, Early Read, reads the data earlier than the specified time period. Our key observation that Early Read causes only unidirectional errors (SET being read as RESET) allows us to efficiently detect data errors using Berger codes. In the uncommon case that Early Read causes data error(s), we simply retry the read operation with original latency. Our evaluations show that Early Read can reduce the read latency by 25% while incurring a storage overhead of only 10 bits per 64 byte line. Our second proposal, Turbo Read, reduces the sensing time for read operations by pumping higher current, at the expense of accidentally switching the PCM cell with small probability during the read operation. We analyze Error Correction Codes (ECC) and Probabilistic Row Scrubbing (PRS) for maintaining data integrity under Turbo Read. We show that a combination of Early Read and Turbo Read can reduce the PCM read latency by 30%, improve the system performance by 21%, and reduce the Energy Delay Product (EDP) by 28%, while requiring minimal changes to the memory system.
Medicinal Plants with Multiple Effects on Cardiovascular Diseases: A Systematic Review.

INTRODUCTION Hyperlipidemia, obesity, hypertension, and diabetes are the most important risk factors for cardiovascular diseases. The aim of this systematic review article is to introduce the medicinal plants that exert significant clinical effects on hypertension, hyperlipidemia, obesity, and diabetes. METHODS In this review article, the international research databases including MEDLINE, Google scholar, EBSCO, Academic Search, Web of Science, SciVerse, Scopus (SCOPUS), EBSCO, Academic Search, Cochrane, Central Register of Controlled Trials (CENTRAL) and a Chinese database (China Network Knowledge Infrastructure [CNKI]) were searched using the key words hyperlipidemia, hypertension, diabetes, herbal, obesity, and phytomedicine, matched by MESH, from their respective inceptions up to March, 2016. The plants that were effective on one, two, three, or all of four diseases were determined. The doses, side effects, the most important pharmaceutically effective compounds, the used organs, and important points regarding usage were separately recorded. Also known clinically significant interactions were presented. RESULTS 1023 articles were found to be about medicinal plants and hypertension, 1912 articles about medicinal plants and hyperlipidemia, 810 articles about medicinal plants and obesity, 1174 articles about medicinal plants and diabetes. Of 144 plants included in the analysis, 83 were found to be effective on hyperlipidemia, 100 on hypertension, 66 on obesity, and 72 on diabetes. 43 plants were found to be effective on two diseases, 14 on three diseases, and 34 on all four diseases. Three plants (Tomato, Cranberry and Pomegranate), in food and therapeutic doses, were found to be used to treat cardiovascular diseases especially in pre-eclampsia and hyperlipidemia in pregnancy. CONCLUSION Regarding the findings of this study, we can argue that the medicinal plants, other than monotherapy, can be used as poly-therapy, to treat cardiovascular diseases.
Mining Halophytes for Plant Growth-Promoting Halotolerant Bacteria to Enhance the Salinity Tolerance of Non-halophytic Crops

Salinity stress is one of the major abiotic stresses limiting crop production in arid and semi-arid regions. Interest is increasing in the application of PGPRs (plant growth promoting rhizobacteria) to ameliorate stresses such as salinity stress in crop production. The identification of salt-tolerant, or halophilic, PGPRs has the potential to promote saline soil-based agriculture. Halophytes are a useful reservoir of halotolerant bacteria with plant growth-promoting capabilities. Here, we review recent studies on the use of halophilic PGPRs to stimulate plant growth and increase the tolerance of non-halophytic crops to salinity. These studies illustrate that halophilic PGPRs from the rhizosphere of halophytic species can be effective bio-inoculants for promoting the production of non-halophytic species in saline soils. These studies support the viability of bioinoculation with halophilic PGPRs as a strategy for the sustainable enhancement of non-halophytic crop growth. The potential of this strategy is discussed within the context of ensuring sustainable food production for a world with an increasing population and continuing climate change. We also explore future research needs for using halotolerant PGPRs under salinity stress.
Whole-Genome Expression Profiling in Skin Reveals SYK As a Key Regulator of Inflammation in Experimental Epidermolysis Bullosa Acquisita

Because of the morbidity and limited therapeutic options of autoimmune diseases, there is a high, and thus far, unmet medical need for development of novel treatments. Pemphigoid diseases, such as epidermolysis bullosa acquisita (EBA), are prototypical autoimmune diseases that are caused by autoantibodies targeting structural proteins of the skin, leading to inflammation, mediated by myeloid cells. To identify novel treatment targets, we performed cutaneous genome-wide mRNA expression profiling in 190 outbred mice after EBA induction. Comparison of genome-wide mRNA expression profiles in diseased and healthy mice, and construction of a co-expression network identified Sykb (spleen tyrosine kinase, SYK) as a major hub gene. Aligned, pharmacological SYK inhibition protected mice from experimental EBA. Using lineage-specific SYK-deficient mice, we identified SYK expression on myeloid cells to be required to induce EBA. Within the predicted co-expression network, interactions of Sykb with several partners (e.g., Tlr13, Jdp2, and Nfkbid) were validated by curated databases. Additionally, novel gene interaction partners of SYK were experimentally validated. Collectively, our results identify SYK expression in myeloid cells as a requirement to promote inflammation in autoantibody-driven pathologies. This should encourage exploitation of SYK and SYK-regulated genes as potential therapeutic targets for EBA and potentially other autoantibody-mediated diseases.
Integrated Modeling and Experimental Studies at the Meso Scale for Advanced Reactive Materials

Abstract : The modeling and simulation work in this grant was directed by Prof. D. Scott Stewart, (the Stewart-Group) and the experimental work and data collection was directed by Prof. Nick Glumac (the Glumac-group). Professors Stewart and Glumac and Drs. John Bdzil and Joseph C. Foster, collaborated on experimental designs, that benefited from the concurrent theoretical and computational modeling. The effort described in this report fully integrated modeling and experiments to study the energy release processes that thermitic and/or exothermic intermetallic reactive materials experience when they are subjected to sustained shock loading.
Genome-Wide Association Mapping for Tolerance to Preharvest Sprouting and Low Falling Numbers in Wheat

Preharvest sprouting (PHS), the germination of grain on the mother plant under cool and wet conditions, is a recurring problem for wheat farmers worldwide. α-amylase enzyme produced during PHS degrades starch resulting in baked good with poor end-use quality. The Hagberg-Perten Falling Number (FN) test is used to measure this problem in the wheat industry, and determines how much a farmer's wheat is discounted for PHS damage. PHS tolerance is associated with higher grain dormancy. Thus, breeding programs use germination-based assays such as the spike-wetting test to measure PHS susceptibility. Association mapping identified loci associated with PHS tolerance in U.S. Pacific Northwest germplasm based both on FN and on spike-wetting test data. The study was performed using a panel of 469 white winter wheat cultivars and elite breeding lines grown in six Washington state environments, and genotyped for 15,229 polymorphic markers using the 90k SNP Illumina iSelect array. Marker-trait associations were identified using the FarmCPU R package. Principal component analysis was directly and a kinship matrix was indirectly used to account for population structure. Nine loci were associated with FN and 34 loci associated with PHS based on sprouting scores. None of the QFN.wsu loci were detected in multiple environments, whereas six of the 34 QPHS.wsu loci were detected in two of the five environments. There was no overlap between the QTN detected based on FN and PHS, and there was little correlation between the two traits. However, both traits appear to be PHS-related since 19 of the 34 QPHS.wsu loci and four of the nine QFN.wsu loci co-localized with previously published dormancy and PHS QTL. Identification of these loci will lead to a better understanding of the genetic architecture of PHS and will help with the future development of genomic selection models.
A Three-Phase Integrated Onboard Charger for Plug-In Electric Vehicles

A three-phase onboard charger, integrated with the propulsion system of a plug-in electric vehicle, is presented. It is constructed by connecting an add-on three-phase power electronics interface to the propulsion system. The propulsion motor is utilized as a coupled DC inductor for the charger. The charging power level of the proposed charger could be as high as that of the propulsion system. The charger topology is capable of three-phase power factor (PF) correction and battery voltage/current regulation. Detailed analyses of the circuit operation and modeling of the circuit are presented. Experimental results of a 3.3-kW three-phase integrated charger, using a permanent magnet synchronous machine (PMSM), are provided. A nearly unity PF and 4.77% total harmonic distortion are obtained with a maximum efficiency of 92.6%.
Migrating Mule Deer: Effects of Anthropogenically Altered Landscapes

Background Migration is an adaptive strategy that enables animals to enhance resource availability and reduce risk of predation at a broad geographic scale. Ungulate migrations generally occur along traditional routes, many of which have been disrupted by anthropogenic disturbances. Spring migration in ungulates is of particular importance for conservation planning, because it is closely coupled with timing of parturition. The degree to which oil and gas development affects migratory patterns, and whether ungulate migration is sufficiently plastic to compensate for such changes, warrants additional study to better understand this critical conservation issue. Methodology/Principal Findings We studied timing and synchrony of departure from winter range and arrival to summer range of female mule deer (Odocoileus hemionus) in northwestern Colorado, USA, which has one of the largest natural-gas reserves currently under development in North America. We hypothesized that in addition to local weather, plant phenology, and individual life-history characteristics, patterns of spring migration would be modified by disturbances associated with natural-gas extraction. We captured 205 adult female mule deer, equipped them with GPS collars, and observed patterns of spring migration during 2008–2010. Conclusions/Significance Timing of spring migration was related to winter weather (particularly snow depth) and access to emerging vegetation, which varied among years, but was highly synchronous across study areas within years. Additionally, timing of migration was influenced by the collective effects of anthropogenic disturbance, rate of travel, distance traveled, and body condition of adult females. Rates of travel were more rapid over shorter migration distances in areas of high natural-gas development resulting in the delayed departure, but early arrival for females migrating in areas with high development compared with less-developed areas. Such shifts in behavior could have consequences for timing of arrival on birthing areas, especially where mule deer migrate over longer distances or for greater durations.
Apoptotic effects of platelet factor VIII on megakaryopoiesis: implications for a modified human FVIII for platelet‐based gene therapy

Ectopically expressed B‐domainless factor VIII in megakaryocytes is stored in α‐granules, is effective in a number of murine hemostatic models, and is protected from circulating inhibitors. However, this platelet (p) FVIII has different temporal–spatial availability from plasma FVIII, with limited efficacy in other murine hemostatic models.
Integrating Design and Data Centric Approaches to Generate Invariants for Distributed Attack Detection

Process anomaly is used for detecting cyber-physical attacks on critical infrastructure such as plants for water treatment and electric power generation. Identification of process anomaly is possible using rules that govern the physical and chemical behavior of the process within a plant. These rules, often referred to as invariants, can be derived either directly from plant design or from the data generated in an operational. However, for operational legacy plants, one might consider a data-centric approach for the derivation of invariants. The study reported here is a comparison of design-centric and data-centric approaches to derive process invariants. The study was conducted using the design of, and the data generated from, an operational water treatment plant. The outcome of the study supports the conjecture that neither approach is adequate in itself, and hence, the two ought to be integrated.
The effect of dietary composition and of insulin on gluconeogenesis in rainbow trout (Salmo gairdneri)

1. The activities at 15° of three gluconeogenic enzymes, d-fructose-1,6-diphosphate, 1-phosphohydrolase (EC 3.1.3.11), pyruvate carboxylase (EC 6.4.1.1) and phosphoenolpyruvate carboxykinase (4.1.1.32), were determined in liver, kidney, gill and muscle of rainbow trout (Salmo gairdneri) given a commercial diet. The results indicated that liver and kidney are the main sites of gluconeogenesis. 2. Glucose formation from pyruvate was approximately 6 μmol/h per g wet weight at 15° in liver slices of trout given a commercial diet. 3. Glucose diffusion space in trout was measured by the dilution principle after intravascular injection of a trace dose of [U-14C]glucose. Glucose space was found to be 13.7% of the body-weight. Gluconeogenesis in vivo amounted to approximately 45 μmol/kg body-weight per h. 4. Intraperitoneally injected [U-14C]alanine was quickly converted to glucose. Maximal incorporation of alanine into glucose occurred 6 h after alanine administration. 5. Rainbow trout given a high-protein diet gained in weight significantly during a 4-week period. Those given a high-carbohydrate diet did not make a significant weight gain over the same period. Gluconeogenesis from alanine was markedly reduced in fish given the high-carbohydrate diet. There was no significant difference in gluconeogenesis from alanine in fish given a high-protein diet and fish which were fasted for 21 d. 6. Gluconeogenesis from alanine in trout was suppressed by intravenous injection of insulin. This effect was found both in trout given a high-protein diet and in fasted trout.
Urinary miR‐155‐5p and CXCL10 as prognostic and predictive biomarkers of rejection, graft outcome and treatment response in kidney transplantation

AIMS MicroRNAs (miRNAs) may be useful biomarkers of rejection and allograft outcome in kidney transplantation. Elevated urinary CXCL10 levels have been associated with acute rejection (AR) and may predict allograft failure. We examined the correlation of miRNA, CXCL10 levels and immunosuppressive drug exposure with AR and graft function in kidney transplant recipients. METHODS Eighty de novo kidney transplant recipients were recruited from four European centres. All patients received tacrolimus, mycophenolate mofetil, and methylprednisolone. Urinary pellet expression of miR-142-3p, miR-210-3p and miR-155-5p was assessed by quantitative real-time polymerase chain reaction and urinary CXCL10 levels by enzyme-linked immunosorbent assay at the 1st week and the 1st , 2nd , 3rd and 6th months post-transplantation. RESULTS Eight patients experienced AR. Before and during AR, patients showed a significant increase of urinary miR-142-3p, miR-155-5p and CXCL10 levels and a decrease of miR-210-3p levels. Receiver operating characteristic curve analysis showed that miR-155-5p (area under the curve = 0.875; P = 0.046) and CXCL10 (area under the curve = 0.865; P = 0.029) had excellent capacity to discriminate between rejectors and nonrejectors. The optimal cut-off values for the prognosis of AR were 0.51, with 85% sensitivity and 86% specificity for miR-155-5p and 84.73 pg ml-1 , with 84% sensitivity and 80% specificity for CXCL10. miR-155-5p and CXCL10 levels correlated with glomerular filtration rate. Levels of both biomarkers normalized after recovery of graft function. CONCLUSIONS The regular early post-transplantation monitoring of urinary miR-155-5p and CXCL10 can help in the prognosis of AR and graft dysfunction. Large prospective randomized multicentre trials are warranted to refine our cut-off values and validate the clinical usefulness of these biomarkers.
Flexible technologies and smart clothing for citizen medicine, home healthcare, and disease prevention

Improvement of the quality and efficiency of healthcare in medicine, both at home and in hospital, is becoming more and more important for patients and society at large. As many technologies (micro technologies, telecommunication, low-power design, new textiles, and flexible sensors) are now available, new user-friendly devices can be developed to enhance the comfort and security of the patient. As clothes and textiles are in direct contact with about 90% of the skin surface, smart sensors and smart clothes with noninvasive sensors are an attractive solution for home-based and ambulatory health monitoring. Moreover, wearable devices or smart homes with exosensors are also potential solutions. All these systems can provide a safe and comfortable environment for home healthcare, illness prevention, and citizen medicine.
Comparison of State-of-Charge estimation methods for stationary Lithium-ion batteries

An accurate monitoring of the State of Charge (SoC) is mandatory for an efficient management of a Lithium-ion battery. Batteries of stationary systems barely have long resting periods when the cumulative errors can be reset. These special requirements make a robust and accurate SoC estimation algorithm necessary. A real stationary system including an experimental microgrid with renewable energy generation, home consumption and a 5.3 kWh Li-ion storage system is analyzed in this paper. Three representative SoC monitoring algorithms are applied and compared in terms of accuracy and robustness to battery aging and current measurement offset. A closed-loop method consisting of an adaptive filter and a state observer achieves best results while having a reasonable computational complexity.