Miracle-dz/UniFAR-FTUs huggingface dataset:
Allegorical Readers and Cultural Revision in Ancient Alexandria

Allegorical readings of literary or religious texts always begin as counterreadings, starting with denial or negation, challenging the literal sense: 'You have read the text this way, but I will read it differently. ' David Dawson insists that ancient allegory is best understood not simply as a way of reading texts, but as a way of using non-literal readings to reinterpret culture and society. Here he describes how some ancient pagan, Jewish, and Christian interpreters used allegory to endorse, revise, and subvert competing Christian and pagan world views. This reassessment of allegorical reading emphasizes socio-cultural contexts rather than purely formal literary features, opening with an analysis of the pagan use of etymology and allegory in the Hellenistic world and pagan opposition to both techniques. The remainder of the book presents three Hellenistic religious writers who each typify distinctive models of allegorical interpretation: the Jewish exegete Philo, the Christian Gnostic Valentinus, and the Christian Platonist Clement. The study engages issues in the fields of classics, history of Christianity and Hellenistic Judaism, literary criticism and theory, and more broadly, critical theory and cultural criticism.
Development of ‘My Meal Mate’ – A smartphone intervention for weight loss

Summary Obesity is a major public health issue and research is turning to information communication technologies as a means to deliver weight management interventions. A smartphone application (app) which allows the user to self monitor food intake and physical activity could be one such convenient and wide reaching approach. A smartphone app called ‘My Meal Mate’ (MMM) has been developed which uses behavioural strategies of goal setting, self monitoring and feedback to aid weight management. The development of the app has been informed by focus groups with potential system users and by benchmarking against popular diet tracking applications available to download. This paper describes the MMM app, discusses its development and outlines plans for further investigation.
Accuracy of shoulder ultrasound examination for diagnosis of rotator cuff pathologies: a single-center retrospective study

ABSTRACT BACKGROUND: Shoulder pathologies need accurate diagnosis for best management and treatment provided to patients. OBJECTIVE: Determine the diagnostic sensitivity, specificity and accuracy of shoulder ultrasonography (US). DESIGN: Retrospective, analytical. SETTING: Tertiary care center in Riyadh, Saudi Arabia. PATIENTS AND METHODS: We included all shoulder exams performed between January 2010 and December 2016 that met the inclusion criteria. Data was collected retrospectively from the a picture archiving and communication system and patient records. The patients were evaluated using US for the presence of rotator cuff tears and classified into intact, full-thickness tear, partial-thickness tear, tendinosis, subacromial/subdeltoid bursitis and acromioclavicular joint degenerative changes. The US findings were correlated with the shoulder MRI study findings. The time interval between the US examination and MRI ranged from 0 to 180 days (6 months). MAIN OUTCOME MEASURES: To compare the sensitivity, specificity and accuracy of shoulder US studies in the detection of rotator cuff pathologies in comparison to MRI findings. SAMPLE SIZE AND CHARACTERISTICS: 86 (60 females, 26 male), mean age 53.7 years (range, 19-85). RESULTS: The sensitivity, specificity and accuracy of US for the detection of full-thickness supraspinatus tears compared with those of MRI were 86%, 82% and 83%, respectively. The sensitivity, specificity and accuracy of US for the detection of partial-thickness supraspinatus tears compared with those of MRI were 38%, 70% and 58%, respectively. Overall PPV, NPV, sensitivity, specificity and accuracy of US for the detection of full-thickness tears compared with those of MRI were 35%, 97%, 78%, 83% and 83%, respectively. For partial-thickness tears, the overall PPV, NPV, sensitivity, specificity and accuracy of US compared with those of MRI were 51%, 60%, 51%, 60% and 56%, respectively. CONCLUSION: Overall, US has high sensitivity, specificity and accuracy for the detection of full-thickness tears compared with the detection of partial-thickness tears. LIMITATIONS: Small sample size and retrospective. CONFLICT OF INTEREST: None.
Angiotensin-converting enzyme inhibitor prescription is associated with decreased progression-free survival (PFS) and overall survival (OS) in patients with lung cancers treated with PD-1/PD-L1 immune checkpoint blockers.

e20512 Background: Angiotensin converting enzyme (ACE) inhibitors are used to treat hyperblood pressure and congestive heart failure. Preclinical evidence show that ACE has a role in both innate and adaptive responses thus suggesting a capacity of ACE to promote antitumor immunity. Interaction between ACE inhibitors and Immune checkpoint blockers (ICB) has not been investigated in cancer patients (pts). Our study evaluated the effect of ACE inhibitors in Non Small cell lung cancer (NSCLC) pts treated with PD-1/PD-L1 inhibitors. Methods: We conducted a retrospective multicohort retrospective analysis of pts treated with PD-1/PD-L1 inhibitors for NSCLC at Dijon Cancer Center, and at the University of Montreal Hospital. ACE inhibitors groups were defined as pts treated with ACE inhibitors given during the treatment with ICB. PFS and OS were compared between both groups among all pts. Statistical analyses were performed using the Kaplan-Meier method and Cox univariate analysis. Multivariate Cox regression analyses was used to adjust for classical prognostic factors. Tumor RNA sequencing were performed and CIBERSORT was used to estimate immune cell infiltration in ACE inhibitors group and None ACE inhibitors group. Results: Among 283 pts included (177 pts from Dijon, and 106 pts from Montreal), 27 (10%) received ACE inhibitors. ACE inhibitors group did not differ from None ACE inhibitors group for main clinical prognostic characteristics. However, ACE inhibitors group are more frequently treated with statin, beta blocker and metformin. ACE inhibitors group had shorter median PFS compared to None ACE inhibitors group : 2.5 vs. 3.8 months, p = 0.02 (HR = 1.7 IC95% 1.1-2.5 p = 0.02 Cox Univariate). The negative impact of ACE inhibitors group was maintained after multivariate analyses adjusting for risk factors (HR = 1.9 IC95% 1.1-3.5 p = 0.02 for PFS and HR = 2.3 IC95% 1.2-4.4 p = 0.01 for OS). RNA sequencing and CIBERSORT analysis underlines that ACE inhibitors group has lower M1 macrophage, activated Mast cells, NK cells and memory activated T cells thus suggesting an immunosuppressive state. Conclusions: ACE inhibitors prescription concomitant to the PD-1/PD-L1 inhibitors treatment impairs the outcome in patients with advanced NSCLC pts. This reduction is independent of classical prognostic factors. Biological date underlines an immunosuppressive state in ACE inhibitors group. These data should be validated in larger cohort.
Eimeria tenella Elongation Factor-1α (EF-1α) Coadministered with Chicken IL-7 (chIL-7) DNA Vaccine Emulsified in Montanide Gel 01 Adjuvant Enhanced the Immune Response to E. acervulina Infection in Broiler Chickens

SUMMARY. The current study was undertaken to assess the vaccine efficacy of Eimeria tenella EF-1α/chicken IL-7 (chIL-7) DNA vaccine when administered with Montanide Gel 01 adjuvant against live Eimeria acervulina challenge in commercial broiler chickens. The criteria used for the evaluation of vaccine efficacy were weight gain, duodenal lesion scores, oocyst counts, humoral antibody response, and duodenal proinflammatory cytokine gene expression. Chickens vaccinated with EF-1α (100 µg)/chIL-7 (20 µg) in Gel 01 PR adjuvant showed body weight gain similar to the uninfected control and higher oocyst shedding, a lower gut lesion score, and higher proinflammatory cytokine gene expression than did the infected controls. Moreover, chickens vaccinated with chIL-7 (20 µg) in Gel 01 PR adjuvant shed fewer oocysts with reduced gut lesion scores and produced higher levels of anti-EF-1α serum antibody than did the infected control. Chickens vaccinated with EF-1α (50 µg)/chIL-7 (20 µg) in Gel 01 PR adjuvant showed higher weight gains than did the infected control and shed significantly fewer oocysts than the infected control. Furthermore, chickens vaccinated with EF-1α (100 µg) in Gel 01 PR adjuvant demonstrated the lowest anti-EF-1α serum antibody levels. This study demonstrated the beneficial effects of using EF-1α and/or host cytokine chIL-7 DNA vaccine together with Gel 01 PR adjuvant to improve T-cell-mediated effector function in broiler chickens challenged with live E. acervulina.
Prophylactic Donor Lymphocyte Infusion to Prevent Relapse after Allogeneic Stem Cell Transplantation

Donor lymphocyte infusion (DLI) has been used to treat disease relapse after stem cell transplantation, but high incidence of graftversus-host disease (GVHD) after traditional DLI, and low response rates with robust relapse in acute leukemia have limited its wide application. Nonetheless, the promising graft versus leukemia effect elicited by DLI makes it a viable option, especially in the state of minimal residual disease after stem cell transplantation. Prophylactic donor lymphocyte infusion has been explored as a more tolerable, less toxic and efficacious option to prevent relapse. This review will summarize the results of the latest prophylactic DLI studies, and discuss our ongoing prophylactic DLI clinical trial after T cell depleted stem cell transplantation in patients with high risk hematologic malignancies.
Evaluation of comprehensive ambulatory rehabilitation of people over 60 years of age

Abstract Introduction. The provision of adequate health care for a successively growing group of geriatric patients requires taking into account many factors in order to preserve and/or improve their overall health and the related functional capacity. Its crucial aspects include the ability to safely change position and locomotion, as well as the severity of discomfort from the osteoarticular system. Aim. The objective of the present study was to assess the impact of comprehensive ambulatory rehabilitation including tailored endurance training, preceded by an ergospirometry test, on indicators showing the risk of falls and the severity of pain symptoms of patients aged 60 and over, receiving health services at the Outpatient Healthcare Home (DDOM). Material and methods. The study involved 60 seniors during their rehabilitation cycle implemented as part of the services provided to patients at DDOM of the W. Chodźko Institute of Rural Health in Lublin. The tests were carried out in the test-retest model on the first and last day of the kinesiotherapy cycle. The Tinetti scale of the risk of falls, balance and walk and Visual Analogue Scale of the severity of pain sensations (VAS) were utilized in the research. The patient rehabilitation program at the DDOM included adapted systemic kinesiotherapy (endurance training with a load determined according to individual exercise capacity, as determined on the basis of the ergospirometry test) and local kinesiotherapy as well as physical therapy adapted to the needs resulting from the condition of the musculoskeletal system. Results. After completing the rehabilitation cycle, the patients obtained higher scores, compared to the tests carried out before the beginning of the rehabilitation cycle, in the scales of Tinetti Questionnaire. There were also lower results of the respondents in VAS scale used to assess the severity of pain sensations. Conclusions. As a result of the rehabilitation program applied, DDOM patients simultaneously obtained the desired changes in minimizing the risk of falls, improving the ability to maintain balance and fitness while walking, as well as reducing the severity of pain sensation.
INTERACTIVE OBJECT SEGMENTATION WITH NOISY BINARY INPUTS

We consider the problem of interactively specifying an object segment in an image in an efficient and robust manner via binary inputs corrupted by noise. Our method frames interactive segmentation as a communications system with feedback and leverages a simple channel coding scheme to allow a user to select a segment from an ordered lexicon of segments for a given image. We propose an intuitive lexicon based on ellipses (EllipseLex) and evaluate its ability to specify desired object segments over increasing numbers of inputs at various levels of input noise, and compare it to a baseline algorithm. After evaluating the performance of each method on the Microsoft Common Objects in Context (MS-COCO) dataset using several metrics, we find that our method exhibits competitive performance when specifying real-world objects in images.
Randomized phase II CLIO study on olaparib monotherapy versus chemotherapy in platinum-resistant ovarian cancer.

5507 Background: The CLIO trial (NCT02822157) evaluated olaparib single-agent therapy versus standard of care chemotherapy in platinum-resistant (recurrence within 6 months after last platin) ovarian cancer (PROC). Methods: Eligible patients with measurable disease and ≥1 prior line of chemotherapy were randomized 2:1 to Olaparib (OLA) monotherapy (300 mg tablets, BID) or physician’s choice chemotherapy (CT; PLD 40 mg/m2 q 4 wks; Topotecan 1.25 mg/m2 day 1—5 q 3 wks; Paclitaxel 80 mg/m2 day 1, 8,15 q 3 wks; Gemcitabine 1000 mg/m2 day 1, 8 and 15 q 4 wks). Primary endpoint was objective overall response (ORR) per RECIST v1.1. Germline BRCA status was available for all patients. Disease control rate (DCR) was defined as response for at least 12 wks. Results: 100 patients with PROC were randomized 2:1 to OLA (N = 67) or CT (N = 33). Median prior lines of treatment was 3 (range: 1—8). ORR (unconfirmed) was 18% (12/67) for OLA and 6% (2/33) for CT. ORR for OLA was 38% (5/13) in gBRCAm and 13% (7/54) in gBRCAwt patients. Of note, 2 patients with gBRIP1 mutation had no response under OLA. DCR was 35.8% (24/67) for OLA and 42% (14/33) for CT. DCR under OLA in gBRCAm was 62% (8/13) compared to 30% (16/54) in gBRCAwt disease. The median duration of response (DOR) and the median progression-free survival (PFS) was similar: 5.4 months vs 4.5 months (DOR) and 2.9 vs 3.4 months (PFS) for OLA and CT, respectively. Grade ≥3 treatment-related AEs occurred in 60% vs 52% for OLA and CT, respectively. Somatic HRR mutation analysis is ongoing and will be presented. Conclusions: Olaparib monotherapy showed a favorable response rate in PROC compared with chemotherapy also in gBRCAwt patients. Analysis of clinical endpoints in relation to HRR is ongoing and will be presented. Clinical trial information: NCT02822157.
An image change detection application for Field Server.

Field Server is a Web server that has a weather station and a camera. It is installed in many fields all over the world, and stores meteorological data and images into the server periodically. The stored images are used to observe the growth of plants and to detect the changes in a field by displaying continuously as animation on a Web browser. Since a standard Field Server camera takes an image every 2 minutes, a total of 720 images are stored for each target area every day. It was becoming difficult to utilize the enormous number of stored images with the simple image viewer application. Then, it was decided to execute image change detection using image processing. Since there is no big change from one periodic image to the next, it is not difficult to detect changes, such as the appearance of a worker or an invader. However, since the target image is an intermittent image, the shaking of branches, the movement of shadows and the sudden ambient illuminant change will be extracted as changes. This problem was solved by using two-dimensional density histogram and local image processing developed by AIST. The program incorporating this algorithm is executed in a server and records the change information including the time, the change area and level in an XML file. As a user interface to allow users to view changes between images, the thumbnail type and the Timeline type are provided. This system is used to appeal the safety of agricultural products by extracting the images of agricultural work and showing them to a consumer, and to monitor the theft of agricultural products and illegal disposal of garbage.
Feasibility of Automated Deep Learning Design for Medical Image Classification by Healthcare Professionals with Limited Coding Experience

Deep learning has huge potential to transform healthcare. However, significant expertise is required to train such models and this is a significant blocker for their translation into clinical practice. In this study, we therefore sought to evaluate the use of automated deep learning software to develop medical image diagnostic classifiers by healthcare professionals with limited coding – and no deep learning – expertise. We used five publicly available open-source datasets: (i) retinal fundus images (MESSIDOR); (ii) optical coherence tomography (OCT) images (Guangzhou Medical University/Shiley Eye Institute, Version 3); (iii) images of skin lesions (Human against Machine (HAM)10000) and (iv) both paediatric and adult chest X-ray (CXR) images (Guangzhou Medical University/Shiley Eye Institute, Version 3 and the National Institute of Health (NIH)14 dataset respectively) to separately feed into a neural architecture search framework that automatically developed a deep learning architecture to classify common diseases. Sensitivity (recall), specificity and positive predictive value (precision) were used to evaluate the diagnostic properties of the models. The discriminative performance was assessed using the area under the precision recall curve (AUPRC). In the case of the deep learning model developed on a subset of the HAM10000 dataset, we performed external validation using the Edinburgh Dermofit Library dataset. Diagnostic properties and discriminative performance from internal validations were high in the binary classification tasks (range: sensitivity of 73.3-97.0%, specificity of 67-100% and AUPRC of 0.87-1). In the multiple classification tasks, the diagnostic properties ranged from 38-100% for sensitivity and 67-100% for specificity. The discriminative performance in terms of AUPRC ranged from 0.57 to 1 in the five automated deep learning models. In an external validation using the Edinburgh Dermofit Library dataset, the automated deep learning model showed an AUPRC of 0.47, with a sensitivity of 49% and a positive predictive value of 52%. The quality of the open-access datasets used in this study (including the lack of information about patient flow and demographics) and the absence of measurement for precision, such as confidence intervals, constituted the major limitation of this study. All models, except for the automated deep learning model trained on the multi-label classification task of the NIH CXR14 dataset, showed comparable discriminative performance and diagnostic properties to state-of-the-art performing deep learning algorithms. The performance in the external validation study was low. The availability of automated deep learning may become a cornerstone for the democratization of sophisticated algorithmic modelling in healthcare as it allows the derivation of classification models without requiring a deep understanding of the mathematical, statistical and programming principles. Future studies should compare several application programming interfaces on thoroughly curated datasets.
The Depth/Breadth Tradeoff in Hierarchical Computer Menus

Goal acquisition speed and accuracy were compared for subjects using four different menu configurations of a semantic hierarchy on an interactive computer terminal. Depth (the number of menu levels) varied from one to six, while breadth (the number of choices per menu) varied from two to 64. Goal acquisition time for the four experimental groups produced a U-shaped function with a minimum at the configuration of two levels with eight choices per level. Error data corroborated the acquisition times demonstrating that the fastest conditions also produced the least errors. Optimization of the depth/breadth tradeoff can be an important design consideration in goal acquisition tasks requiring speed and accuracy.
SIMULATION ANALYSIS OF DAILY SERVICE DELAY FOCUSING ON TRAIN HEADWAY

Small irregularities in service are leading to significant delays in the urban railway system of Tokyo, Japan, because the rail system is now operating very close to its capacity. The delay factor, however, var-ies by hour. The increase in train running time becomes the major cause during the later rush hours, which is longer than that of dwelling time. However, because there is limited data availability concerning the behavior of train under the delay, the case of the delay time increase due to an interaction between trains is not properly accounted. No research has yet been carried out to specifically examine a practically feasible operating method which can recover the knock-on delay early. Therefore, this research formu-lated a train operation simulation model which reproduces the behavior of train operation taking into ac-count the interaction between the trains. Using this simulation model, this study attempted to grasp an ac-tual situation of train operation under the knock-on delay, and suggested a practically method to recover the knock-on delay earlier, which involves keeping the moderate separation between trains during running time.
DISTRIBUTED SDR APPLICATIONS FOR DISTANCE LEARNING

A business card that contains printed textual information on the first side and magnetic media for storing electronic information on a second side. The second side contains all of the printed information displayed on the first side of the document. The business card also allows users to include additional information on the second side such as attached files and hyperlinks. To write and read to and from the business card, a reader/writer is disclosed. The reader/writer interfaces to a desktop computer. A software program in the personal computer enables reading and writing data to and from the business card. Because the data to be read is in XML format, any application capable of handling data in XML format will be able to process the information scanned from the card.
Bit-Interleaved Coded Modulation: Fundamentals, Analysis and Design

Presenting a thorough overview of bit-interleaved coded modulation (BICM), this book introduces the tools for the analysis and design of BICM transceivers. It explains in details the functioning principles of BICM and proposes a refined probabilistic modeling of the reliability metrics–the so-called L-values–which are at the core of the BICM receivers. Alternatives for transceiver design based on these models are then studied. Providing new insights into the analysis of BICM, this book is unique in its approach, providing a general framework for analysis and design, focusing on communication theoretic aspects of BICM transceivers. It adopts a tutorial approach, explains the problems in simple terms with the aid of multiple examples and case studies, and provides solutions using accessible mathematical tools. The book will be an excellent resource for researchers in academia and industry: graduate students, academics, development engineers, and R & D managers. Key Features: Presents an introduction to BICM, placing it in the context of other coded modulation schemes Offers explanations of the functioning principles and design alternatives Provides a unique approach, focusing on communication theory aspects Shows examples and case studies to illustrate analysis and design of BICM Adopts a tutorial approach, explaining the problems in simple terms and presenting solutions using accessible mathematical tools