Miracle-dz/UniFAR-FTUs huggingface dataset:
Gallbladder Disease in Type-2 Diabetes Mellitus Patients

Background: Diabetes mellitus is a modern epidemic which leads to various complications over a period of time. Autonomic neuropathy is one such complication which may lead on to gallbladder dysmotility and gallbladder stones. Objectives: To determine the incidence of gallbladder disorders in patients of type 2 diabetes mellitus and to find out the incidence of autonomic dysfunction in type 2 diabetes mellitus and correlate it with presence of gall bladder disorders. Material and Methods: The present study was conducted in 50 cases of type 2 diabetes mellitus and 25 healthy age and sex matched normal individuals were taken as controls. The cases as well as the controls underwent ultrasonographic examination for gall bladder volume, wall thickness, intraluminal mass and contraction in response to fatty meal. Data thus collected was compared and analysed statistically by using students ‘t’ test and chi- square test. Results: Mean postprandial gallbladder volume was 20.56±8.87 cm 3 in diabetics with ANP with gallstones, 26.16±1.24 cm 3 in diabetics with ANP with dysmotility 13.0±6.26 cm 3 in diabetics with gallstones without ANP, 12.14±4.88 cm 3 in normal diabetics and 13.60±5.95 cm 3 in controls. The percentage contraction post fatty meal was calculated from these values and found to be 24.73±14.64% in diabetics with ANP with dysmotility, 26.38±17 . 04% in diabetics with ANP with dysmotility, 43.48±8.45% in diabetics with gallstones without ANP, 56.84±9.02% in normal diabetics and 57 . 64±9.92% in controls. Conclusion: Incidence of gallbladder disease is much higher in type 2 diabetics (40%) as compared to normal healthy adults (4%). It was concluded that diabetics with ANP had significantly impaired gallbladder emptying. Poor control of diabetes, hypercholesterolemia and diabetic autonomic neuropathy are important risk factors for the development of gallbladder disease.
Nanocomposite Polymer Scaffolds Responding under External Stimuli for Drug Delivery and Tissue Engineering Applications

The blossoming development of nanomaterials and polymer science has opened the way toward new biocompatible scaffolds responding remotely to external stimuli (magnetic field, light, electric field). Such smart scaffolds are envisioned as new implantable tissues displaying multiple therapeutic and imaging functionalities. They hold great promises to achieve a controlled delivery of therapeutics for various diseases, or to ensure a stimuli‐induced cellular response for bone, cardiac, or muscle tissue engineering.
Revisión de las novedades del XXXII Congreso ECTRIMS 2016, presentadas en la IX Reunión Post-ECTRIMS (I)

Reconocidos especialistas nacionales en esclerosis multiple (EM) se han reunido, por octavo ano consecutivo, para exponer lo mas novedoso que se presento en la ultima edicion del congreso ECTRIMS 2015 y que recoge esta revision. En esta edicion ha destacado la nueva clasificacion de los fenotipos de la EM. Tambien se revisaron los criterios diagnosticos del espectro de la neuromielitis optica y los problemas en el diagnostico diferencial derivados de la falta de definicion del espectro radiologico. La microbiota adquiere protagonismo como posible factor determinante de la enfermedad, junto con factores extrinsecos como el tabaco, la ingesta de sal o el deficit de vitamina D. Los avances en inmunomodulacion impulsan el progreso en el tratamiento de la EM. El ocrelizumab es el primer tratamiento con resultados positivos en las formas primariamente progresivas, y el tocilizumab, un farmaco para la artritis reumatoide, destaca como candidato potencial para el tratamiento de la neuromielitis optica. Ciertos antibioticos y vitaminas tambien podrian tener un papel en el tratamiento de la EM. En esta edicion se presto especial atencion a la terapia personalizada. Actualmente disponemos de 11 farmacos aprobados en Europa. Se necesitan algoritmos terapeuticos que nos ayuden a elegir el mejor tratamiento para cada paciente. Asimismo, necesitamos poder identificar en los estadios precoces de la enfermedad el riesgo de desarrollar discapacidad, para disenar estrategias terapeuticas, para lo que se precisan biomarcadores moleculares y otras herramientas pronosticas. Los problemas aun existentes en la tecnologia del software en resonancia magnetica dificultan su traslacion a la practica clinica diaria.
A New Improved Baum-Welch Algorithm for Unsupervised Learning for Continuous-Time HMM Using Spark

: Hidden Markov Models are widely used for time continuous problems modelling and prediction. This paper presents two new improved algorithms for Gaussian continuous and mixture of Gaussian continuous Hidden Markov Models cases for solving learning problem for large scale multidimensional data. The design of our parallel distributed algorithms is based on Spark, the Big Data framework, thereby we can distribute data over several nodes through Resilient Distributed Datasets which allow to apply, in parallel, a set of operations. The proposed algorithms have two main advantages: a high computational time efficiency and a high scalability as well as an easy integration in Big Data frameworks. The complexity comparison results show great improvements in computational complexity (by a factor of (states number) 2 ) and execution time. Moreover, the new algorithms might be more effective by reducing the communication costs between the elements of the system involved in the learning task.
Nomograms to predict prognosis of hepatocelluar carcinoma without major vascular invasion after primary liver transplantation

// Junyi Shen 1, * , Chuan Li 1, * , Jun Wen 2 , Tianfu Wen 1 , Lvnan Yan 1 , Bo Li 1 , Jiayin Yang 1 and Highness Tholakkara Nazar 1 1 Department of Liver Surgery and Liver Transplantation Center, West China Hospital, Sichuan University, Chengdu, China 2 Department of General Surgery, The Third People’s Hospital of Chengdu, Chengdu, Sichuan Province, China * These authors contributed equally to this work Correspondence to: Tianfu Wen, email: cdwentianfu@126.com Keywords: nomogram; prognosis; hepatocelluar carcinoma; liver transplantation Received: May 23, 2017 Accepted: January 02, 2018 Published: January 02, 2018 ABSTRACT Background: A model to predict individual prognosis after liver transplantation (LT) has not been clearly established. We aimed to create nomograms for prediction of individual survival after LT for hepatocelluar carcinoma (HCC). Results: There were 128(61.2%) patients within the Milan criteria. Before transplantation, 43 (20.6%) patients received transcatheter arterial chemoembolization (TACE) and 22 (10.5%) received radiofrequency ablation(RFA). Multivariate predictors of survival included tumor size, tumor number and tumor differentiation. Nomograms for OS and recurrence free survival (RFS) have been created. Discrimination and calibration of the nomograms revealed good predictive abilities(C-index, RFS: 0.74; OS: 0.70). Compared with Milan criteria, UCSF criteria, up-to-seven criteria and Hangzhou criteria, the OS nomogram improved accuracy in predicting prognosis after transplantation for HCC, ( p < 0.05 for all). Finally, three subgroups were generated based on the total risk points (A’: 1.88–76.5 points; B’: 76.6–113.9points; C’: 113.9–151.3points). The 5-year survival rate were 86.1% for group A’, 59.1% for group B’, and 28.9% for group C’, respectively. Conclusions: The nomograms had good ability in predicting prognostic survival for HCC patients after LT. Patients with score above 113.9 points had poor survival after LT. Materials and method: Between Juanuary 2002 and September 2015, 209 HCC patients who received liver transplantation in the West China Hospital were collected for this study. Prognostic nomograms predicting post-transplant prognosis were developed from a multivariate cox regression. The prediction power of the nomograms was tested by C-statistic and calibration plots.
Schemes and applications for binding hardware and software in computing devices

The Internet of Things (IoT) is considered one of the most significant computing trends of the 21st century so far, causing the number of deployed computing devices to increase dramatically. However, the frequency and severity of attacks against computer systems is increasing with attacks such as Stuxnet and Mirai. This thesis is concerned with securing computing devices by creating bonds between hardware and software to ensure deployed devices only execute the software they are intended to and vice versa. This prevents counterfeiting, device tampering and other attacks. This thesis presents three studies into binding hardware and software. These concern creating secure dependencies between the hardware and software of computing devices. Specifically, this thesis considers mutual dependencies created by bidirectional bonds between hardware and software. The first study defines hardware-software bonds, the problem space and proposes the first bidirectional scheme for binding hardware and software together. The scheme is implemented using an FPGA and analysed for security and performance. The second case considers the deployment of binding schemes. This is considered in a smart city environment by first studying and modelling the security architecture of the problem. Two security models are proposed with associated software provisioning protocols. All the proposals are formally analysed using Tamarin Prover and implemented for Raspberry Pi and laptop computer. The third study combines hardware-software binding with another problem in cyber security Secure Application Execution. The two problems are compared and set of requirements for simultaneously achieving both is defined. A binding scheme is proposed solving the expanded problem and a prototype Secure Execution Processor equipped with the scheme is presented and analysed. Finally, the thesis concludes by summarising the research presented and highlighting potential areas for future work in binding hardware and software together.
Workload profiles prior to injury in professional soccer players

ABSTRACT This study examined if a particular profile of internal and external workload existed prior to injury. Forty-five professional soccer players were monitored over two seasons. For each non-contact injury, a profile of workload variables was determined for 4 weeks and expressed as (i) an absolute, (ii) week-to-week change and (iii) relative to the player’s season mean. Variables included exposure, session rating of perceived exertion (s-RPE) workload, total distance, low-, high-, very-high-speed running distance, mean speed, bodyload, monotony and strain. Acute:chronic workload ratio was also calculated and sensitivity of the relative workload was tested. Absolute and relative exposure and s-RPE workload were greater in all 3 weeks compared to the injury week (P < 0.05). However, no significant differences were evident between the 3 weeks prior to injury for all variables (P > 0.05). Acute:chronic workload ratio for s-RPE was significantly greater than acute:chronic workload ratio for very-high-speed running (P = 0.04). A workload threshold of 114% of a player’s season mean reported low sensitivity and specificity for exposure (25.6[20.2–33.5]% and 73.9[22.6–28.2]%,) and s-RPE workload (16.3[12.6–24.9]% and 79.9[20.3–26.1]%, respectively). No specific load profile existed, although high-sustained exposure and s-RPE were evident for the 3 weeks prior to injury. Consequently, load prescription should be aware of sustained high workloads.
Healthcare-seeking behavior among diabetic patients in Kozhikode, Kerala -

Background: Diabetes mellitus is a global health problem. India has additional unique problem of treatment compliance of diabetic patients. Diabetic patients do not adhere to treatment and ultimately develop multiple chronic complications leading to irreversible disability and death. Objectives: To determine healthcare--seeking behavior and the health expenditure incurred for the treatment of diabetes in study population. Materials and Methods: Community-based cross-sectional study was conducted in 2015. House-to-house survey was done for data collection. A structured questionnaire was used for collecting data after explaining purpose of the study. All individuals with diabetes residing in area who consented for participation in the study were included in the study. Elderly individuals who were critically ill and were unable to comprehend questions were excluded from the study. Collected data were entered in Microsoft Excel and statistical analysis was done using SPSS version 16. Results: A total of 79 diabetic patients were interviewed. Their mean age was 61.51 ± 11.8 years. 63.3% individuals belonged to upper socioeconomic class. Family history of diabetes was seen in 39.2% of the individuals. Only 34.1% patients used Government health facilities. 82.3% individuals were taking treatment regularly. Comorbidities associated with diabetes were seen in 69.6% of the individuals. The mean total monthly expenditure required for diabetes care was Rs. 1793. Conclusions: Healthcare-seeking behavior among diabetic patients in Kerala is still low compared to diabetic patients in developed countries. Diabetic patients have to spend significant amount for traveling, consultation, and laboratory investigations along with expenditure for drugs and hospitalization.
Characteristics and injury severity score of childhood injuries at Emergency Department of Suez Canal University Hospital

Injury is a leading cause of death and disability among children worldwide, Injury surveillance provides an understanding of the incidence, trends, and magnitude of injuries, identifies specific populations that have a higher incidence of injuries. To describe characteristics of childhood injuries and injury severity score of different types of childhood injuries at emergency department of Suez Canal University Hospital. A cross-sectional analytic study at emergency department in Suez Canal University Hospital targeted children aged ≤ 18 years presented with an injury from June 2013 to April 2014. The tool in the study was Global Childhood Injury Surveillance Instrument to interview the parents or guardians arriving with injured children. Of the total of 402 injured children, about 68.6% of motor car accidents (MCA) were males, (47.2%) occurred in children aged 12-18 years. MCA had the highest Injury severity score (ISS) which was 29.2±2.6. Most of falls (66.1%) occurred in children aged less than 6 years. 26.2% of burn had permanent disability and ISS of burn was 14.5±1.3. Most of accidental poisoning (78.8%) occurred in children aged less than 6 years with female predominance (63.6%). About 85% of poisoning had no significant disability. Childhood intentional injury represented 5.7% of all injuries and had ISS of 8.5±7.7. Falls are the leading cause of injury-related hospitalizations and emergency department visits among children in Suez Canal University Hospital (29.4%), while motor vehicle traffic crashes are the leading cause of death (57%).
Carbonated Inheritance in the Eastern Tibetan Lithospheric Mantle: Petrological Evidences and Geodynamic Implications

The timing and mechanism of formation of the Tibet Plateau remain elusive, and even the present‐day structure of the Tibetan lithosphere is hardly resolved, due to conflicting interpretations of the geophysical data. We show here that significant advances in our understanding of this orogeny could be achieved through a better assessment of the composition and rheological properties of the deepest parts of the Tibetan lithosphere, leading in particular to a reinterpretation of the global tomographic cross sections. We report mantle phlogopite xenocrysts and carbonate‐bearing ultramafic cumulates preserved in Eocene potassic rocks from the Eastern Qiangtang terrane, which provide evidence that the lithospheric mantle in Central Tibet was enriched in H 2 O and CO 2 prior to the India‐Asia collision. Rheological calculations and numerical modeling suggest that (1) such metasomatized mantle would have been significantly weaker than a normal mantle but buoyant enough to prevent its sinking into the deep mantle; (2) the slow seismic anomalies beneath Central Tibet may image a weakened lithosphere of normal thickness rather than a lithosphere thinned and heated by the convective removal of its lower part; and (3) melting of such soft and fusible metasomatized mantle would have been possible during intracontinental subduction, supporting a subduction origin for the studied Eocene potassic magmatism. These results demonstrate that the inheritance a soft and buoyant precollisional Tibetan lithosphere may have conditioned the growth and the present‐day structure of the Tibet Plateau.
Learning Deep Conditional Target Densities for Accurate Regression

While deep learning-based classification is generally tackled using standardized approaches, a wide variety of techniques are employed for regression. In computer vision, one particularly popular such technique is that of confidence-based regression, which entails predicting a confidence value for each input-target pair (x,y). While this approach has demonstrated impressive results, it requires important task-dependent design choices, and the predicted confidences lack a natural probabilistic meaning. We address these issues by proposing a general and conceptually simple regression method with a clear probabilistic interpretation. In our proposed approach, we create an energy-based model of the conditional target density p(y|x), using a deep neural network to predict the un-normalized density from (x,y). This model of p(y|x) is trained by directly minimizing the associated negative log-likelihood, approximated using Monte Carlo sampling. We perform comprehensive experiments on four computer vision regression tasks. Our approach outperforms direct regression, as well as other probabilistic and confidence-based methods. Notably, our model achieves a 2.2% AP improvement over Faster-RCNN for object detection on the COCO dataset, and sets a new state-of-the-art on visual tracking when applied for bounding box estimation. In contrast to confidence-based methods, our approach is also shown to be directly applicable to more general tasks such as age and head-pose estimation.
Transforming The Academy: Black Women Leaders At Predominantly White Institutions In The South

The presence of Black women senior-level leaders in higher education is minimal and their presence in leadership positions at Predominantly White Institutions (PWIs) is abysmal. When and where Black women hold these leadership positions, little is known about their experiences. Consequently, this study centers the lived experiences of seven Black women higher education leaders at PWIs in the U.S. South. Through the intersecting lens using Critical Race Theory and Black Feminist Thought, this qualitative, critical event narrative study examined (1) how race, gender, and culture influenced Black women’s journeys toward obtaining a senior leadership position, (2) the leadership experiences of these leaders, (3) the challenges, barriers, and experiences that have confronted them, and (4) the strategies they have employed when confronting these challenges. This study also underscores the importance of exploring Black women’s perceptions of their leadership experiences within PWIs. These findings have implications for positive change by increasing awareness among executive leaders in the academy regarding racial and gender inequalities. This awareness has the propensity to decrease workplace disparities for Black administrators and to foster more conducive environments to promote more Black women into senior-level leadership positions.
Effect of Heifers Age at First Breeding and Calving on Some Performance Traits and Economic Returns in Friesian cows in Egypt

The primary data used an actual study on 874 Friesian cows management from birth to end lifetime production was collected of El- Karada and Sakha Farms pertain to the Animal Production Research Institute (APRI), from 1990 to 2016. These data were analyzed to determine genetic parameters with REML using animal model and using a general linear model of SAS to determine the main effects. Means of MY, LTMY, LP NLC, AFB, AFC DO, CI, CFB, CFC, LTC, LPP and NP were 3571.63 kg, 17538.70 kg, 303.66 d, 3.48, 31.02month, 40.11month, 77. 54 d, 360.97 d, $961.63, $1259.73, $4638.59, $4858.78 and$1478.58, respectively. The highest rate of culling was in third parity 24.10% following by second parity of 23.59%. Direct heritability of MY, LTMY, LP NLC, AFB, AFC DO and CI was 0.57, 0.31, 0.35, 0.29, 0.38, 0.41, 0.13 and 0.09, respectively. Appraising genetic correlations between aforesaid feature were between (-0.54 to 0.53), the same features phenotypic correlations between same features were from (-0.46 to 0.22). That introduces the major possibility of improvement genetic and optimization management for MY, LTMY, LP, NLC, AFB and AFC. While possibility improvement DO and CI through optimization management. Therefore, management can play a major role in improving these traits. Reducing AFB and AFC bring about to decrease the direct rearing costs subsequently decrease total costs in lifetime vice versa increase LTMY, LPP, and NP. Therefore, it is the best to select replacement heifer for AFB or AFC so that maximum lifetime milk yield and net profit in Friesian farms.
Low temperature tolerance of Plodia interpunctella, Sitophilus oryzae and Sitophilus zeamais: The prevalent pests of stored maize in Serbia

Insect’s bionomics and development are highly dependent on the environmental temperature. For centuries, this fact has been used for the control of storage pests. However, the temperature threshold depends on the species, life stage, acclimation and exposure period. This work assessed the effects of low temperatures (4, -4, -10, -15 and -18°C) and exposure period (10, 30, 60, 120 and 180 min) on the survival and development of Plodia interpunctella larvae, and adults of Sitophilus oryzae and S. zeamais, the prevalent maize pests in Serbia. Data were analysed using one-way and two-way ANOVA. Additionally, Probyt analysis was performed to determine the LT50 and LT99. The first significant effects were recorded at -4°C for S. oryzae when the mortality was 41% after 120 and 52% after 180 min of exposure. At -10°C, the mortality of S. zeamais was significant after 180 min (52.5%) and increased with the exposure period. The significant mortality of P. interpunctella larvae was at -15°C after 10 min (55.5%). At -18°C, P. interpunctella larvae were the most susceptible and 98% of mortality was recorded after 10 min, while 77.5% of S. oryzae and 68% of S. zeamais was recorded after 10 min. Twoway ANOVA showed that both factors (temperature and exposure) significantly affected the mortality of tested species, but the first factor was the most influential. These results indicate that temperature and exposure period should be adjusted to specific pest, while in combined infestations the temperature should be adjusted to the most tolerant one. Received 7 October 2019 Accepted 24 December 2019 Acta Agriculturae Serbica, Vol. XXIV, 48(2019); 143-155 144