Miracle-dz/UniFAR-FTUs huggingface dataset:
First-in-human phase I trial of the combination of two adenoviral vectors expressing HSV1-TK and FLT3L for the treatment of newly diagnosed resectable malignant glioma: Initial results from the therapeutic reprogramming of the brain immune system.

2019 Background: This is the initial report on a first in human Phase I dose escalation trial of the combination of two adenoviral vectors expressing HSV1-TK or Flt3L for the treatment of newly diagnosed, resectable malignant gliomas. The absence of functional dendritic cells from the brain precludes anti-brain tumor immune responses. We combined tumor cytotoxicity (Ad-HSV1TK) with recruitment of dendritic cells to the brain (Ad-Flt3L) to induce an effective anti-tumor immune response. This strategy induced an efficacious, cytotoxic CD8 and CD4 T-dependent immune response in many animal models of glioma. This immune response also generated anti-tumor memory, and the capacity for neoantigen recognition. Methods: The trial was approved by FDA and all institutional cttees. Treatment was administered intraoperatively following complete glioma resection in newly diagnosed tumors. The trial consisted of vector dose escalation, starting at 1x10^9 i.u. , and increasing to 1x10^11 i.u. of each vector. Dose escalation proceeded by increasing the vector dose through a total of 6 combinations administered to 6 cohorts of 3 patients each. Two cycles of 14 days each of valacyclovir were administered to activate HSV1-TK cytotoxicity. Cycle 1 starts on Day 1-3 post surgery for 14 days, and Cycle 2 on Week 8-12. Standard radiation, i.e., 60 Gy in 2 Gy fractions over 6 weeks, with concurrent temozolomide, was followed by cyclic temozolomide. Results: Examination of tumor samples at primary resection and first recurrence show an increase in the infiltration of inflammatory cells. The experimental treatment was well tolerated. At this time the MTD has not been reached. There were approx. 248 AEs, and 26 SAEs; these have not been linked to treatment. At this time the MTD has not been reached. A secondary outcome is overall survival. Preliminary analysis of partial data may suggest that the combined viral vector therapy may provide a clinically significant survival. Conclusions: Our results show for the first time that reprogramming of the host’s brain immune system to recognize gliomas reveals a new approach for the treatment of highly malignant brain tumors. Clinical trial information: NCT01811992.
Epithelial ovarian tumours of low malignant potential.

: The available literature and the management of epithelial tumours of low malignant potential (LMP) is reviewed. The criteria for a diagnosis of LMP at the University of the Witwatersrand are delineated in detail. Based on the records in the Ovarian Tumour Registry of this University, experience with 29 such tumours over 4 years is presented. Of these, 14 (48.3%) were of the serous variety, 12 were mucinous (41.4%), and 2 (6.9%) were mucinous-serous, the remaining 1 (3.4%) being endometrioid. LMP tumours accounted for 12.9% of proliferating epithelial ovarian tumours in black patients compared with 16.9% in white patients. Pelviperitoneal cytological washings for detection of malignant cells in patients with LMP tumours is mandatory.
Web Access Patterns of Actual Human Visitors and Web Robots: A Correlated Examination

Web robots are autonomous software agents used for crawling websites in a mechanized way for nonmalicious and malicious reasons. With the popularity of Web 2.0 services, web robots are also proliferating and growing in sophistication. The web servers are flooded with access requests from web robots. The web access requests are recorded in the form of web server logs, which contains significant knowledge about web access patterns of visitors. The presence of web robot access requests in log repositories distorts the actual access patterns of human visitors. The human visitors’ actual web access patterns are potentially useful for enhancement of services for more satisfaction or optimization of server resources. In this chapter, the correlative access patterns of human visitors and web robots are discussed using the web server access logs of a portal.
Serum Levels of Tumor Necrosis Factor-α (TNF-α), Interleukin-6 (IL-6), and Interleukin-1β (IL-1β) in Dengue-Infected Patients

Abstract Sensitive immunoenzymatic assays were used to study the levels of tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), and IL-1β in sera from dengue-infected patients obtained during the 1989–1990 outbreak of dengue-3 in Tahiti, French Polynesia. The patients, both children (n = 47) and adults (n = 18), were clinically classified as having dengue hemorrhagic fever (DHF) and graded according to the severity of illness (grade I = fever, grade II = fever with spontaneous hemorrhagic manifestations, grade III = circulatory failure, grade IV = deep shock). The serum samples were obtained from day 1 to day 10 after the onset of the disease. High levels of TNF-α were observed in dengue-infected children of all severity grades. The highest values of TNF-α were found before day 6 after the onset of the infection, these values decreased from day 6 to day 10. The highest values were observed in sera from grade III and IV patients. High values of IL-6 were observed in serum samples of grade I and II patients on day 1, which decreased on day 4, and by day 5 were similar to those obtained from 25 control children. In grade III and IV patients, the highest values of IL-6 were observed from day 3 to day 5 after the onset of infection; after day 5, these values were very low. The highest values of IL-6 in grade III patients were accompanied by elevated values of TNF-α and were observed in serum obtained on the day the patient went into shock (dengue shock syndrome [DSS]). The IL-6 values were normal one day before and one day after the patient went into shock. The values of IL-1β were similar to those of 25 control children. Serum samples from dengue-infected adults, obtained from day 4 to day 10 after the onset of disease, showed moderately high levels of TNF-α compared with those of dengue-infected children. In some adult patients, IL-6 values increased and in all the patients, IL-1β values were similar to those of healthy adults. Our results show an inconsistency in TNF-α and IL-6 production in dengue-infected patients that probably has important implications in the physiopathology of DHF/DSS.
A comparison of recursive and repetitive models of recursive hardware structures

This paper examines techniques for developing VHDL descriptions of recursive hardware structures, using recursive and repetitive component instantiations. A fat tree interconnection network is examined as an example of a recursive hardware structure. The recursive description is easier to develop, and more clearly express the structure, making it easier to understand. The main difficulty in developing repetitive structures lies in devising a way of interconnecting the basic components comprising the structure. It is shown that the difficulties result from fundamental language design decisions made in VHDL, and that it is not appropriate to modify the language to avoid the difficulties. Hence, in general, the recursive style is preferred over the repetitive style for describing recursive hardware structures. <<ETX>>
Collision detection algorithm for collaborative robots considering joint friction

This article proposes a collision detection algorithm without external sensors that can detect potential collisions in man–robot interaction. The algorithm is based on a modified first-order momentum deviation observer that also takes friction into account. The collision detection algorithm uses joint angles, angular velocities, and torques during the detection process, without any need to consider angular acceleration. The algorithm also uses an accurate friction model that is based on a Stribeck model with second-order Fourier series compensation. The friction model is applied in advance so that compensation can be made in real time during collision detection. Identification data are filtered through a first-order low-pass filter to reduce high-frequency noise. In order to verify the algorithm, a simulation and experiment were carried out using a collaborative robot experimental platform. The results confirmed that collisions can be detected by setting appropriate threshold values. Different possible responses can be implemented according to different response strategies, with the ultimate arbiter being that collision forces are kept strictly within ordinary human tolerances. This makes sure that safety can be preserved in man–robot interaction processes.
Analisis Deep Learning Untuk Mengenali Qrs Kompleks Pada Sinyal Ecg Dengan Metode Cnn

Abstrak QRS kompleks adalah bentuk umum dari sinyal EKG yang normal dan berhubungan dengan deplarisasi ventrikel. QRS kompleks dapat mendeteksi kelainan frekuensi, keteraturan, tempat asal atau kondisi impuls listrik pada jantung. Namun, pendeteksian QRS kompleks saat ini masih dilakukan manual oleh dokter. Pada Tugas Akhir ini, Dataset yang digunakan diambil dari Fantasia Database MIT Arrythmia. Puncak gelombang R di deteksi menggunakan algoritma Pan and Tompskins lalu dari hasil deteksi data ECG di ekstrak menjadi dataset QRS dan nonQRS yang ditandai dengan kelas 1 dan kelas 0. Dataset ini kemudian diolah dengan metode Deep Learning menggunakan algoritma Convolutional Neural Network. Hasilnya, dengan 2410 dataset dengan komposisi 50% QRS dan 50% non QRS serta membagi data training sebanyak 70% dan data test sebanyak 30%, hasil akurasi yang diperoleh mencapai 99.58%. Kata kunci : Sinyal ECG, QRS Kompleks algoritma Pan and Tomskins, Convolutional Neural Network Abstract QRS complexes are a common form of normal ECG signals and are associated with ventricular deplaration. Complex QRS can detect abnormalities of frequency, regularity, place of origin or electrical impulse conditions in the heart. However, the current complex QRS detection is still performed manually by doctors. In this Final Project, the dataset used is taken from Fantasia MIT Arrythmia Database. R peaks is detected using the Pan and Tompskins algorithm and then the extracted results into QRS and nonQRS datasets characterized by classes 1 and 0. This dataset is processed by Deep Learning method using the Convolutional Neural Network. The result, with 2410 datasets with 50% QRS and 50% non QRS composition and 70% training data sharing and 30% test data, 99.58% accuracy. Keywords : ECG Signal, QRS Complex, Pan and Tomskins Algorithm, Convolutional Neural Network.
Glucose Levels and Risk of Dementia

Further inves-tigation will be required to address the question of whether the inflammatory conditions associ-ated with the development of pneumonia or the use of mechanical ventilation can explain anas-tomotic leak.Mynbaev et al. ask about the possible influ-ence of laparoscopic surgery on the occurrence of the primary outcome. Data presented for laparo -scopic surgery in Table S1 of the Supplementary Appendix of our article (available at NEJM.org) were erroneously interchanged with the data for nonlaparoscopic surgery. The primary outcome measure should have been shown for 10 of the 85 patients who underwent laparoscopic surgery rather than for 69 of those 85 patients (odds ratio, 0.50; 95% confidence interval, 0.25 to 1.03; P=0.06) and for 66 of the 315 patients who un-derwent nonlaparoscopic surgery. We regret the error; a corrected version of the Supplementary Appendix is available at NEJM.org. Emmanuel Futier, M.D., Ph.D.Bruno Pereira, Ph.D.
An index based load balancer to enhance transactional application servers' QoS

The Web is the preferred interface for the new generation of applications. Web services are an ubiquitous concept for both, developers and managers. These Web applications require distribution systems of web requests that allow and support the dynamism of these environments, to provide service availability and resource usage, commonly heterogeneous. Web services provide an entry point to the Web application business logic. Therefore, the design of appropriate load balancing strategies, taking into account the dynamic nature of the application servers' activity, is essential. In this work we present a load balancing policy and its integration inbetween static and dynamic layers of any web application that uses application servers. The strategy gets the status report of each application server, used to later distribute web requests. Results that show how the strategy succeed are presented. KeywordsQoS; web applications; load balancing; application servers.
A SMART METER DESIGN AND IMPLEMENTATION

In this paper Wireless Sensor Home Area Network (WSHAN) with IOT interfaced sensible meter is established along with implemented. As a result of the increasing requirements on electric power, typical electric grid ought to be altered with wise, resilient, trusted as well as additionally pricey effective smart grid applications. Wireless Sensor Networks (WSN) has a crucial task to develop trustworthy in addition to costly reliable smart electric power grid applications. Our system establishes power usage logs details online as well as likewise exposes time of use well worth's. The system furthermore handles any type of sort of device connected to power end results. While powering on along with off, zero-cross of Air Conditioner signal is detected to figure out phase modification. The sensible meter provides appropriate power usage in addition to transfer’s details with WIFI to COMPUTER (Personal Computer). The private checks the power information as well as likewise from one more place manages the system. Normal 0 false false false EN-IN X-NONE TE MicrosoftInternetExplorer4 : In this paper Wireless Sensor Home Area Network (WSHAN) with IOT interfaced sensible meter is established along with implemented. As a result of the increasing requirements on electric power, typical electric grid ought to be altered with wise, resilient, trusted as well as additionally pricey effective smart grid applications. Wireless Sensor Networks (WSN) has a crucial task to develop trustworthy in addition to costly reliable smart electric power grid applications. Our system establishes power usage logs details online as well as likewise exposes time of use well worth's. The system furthermore handles any type of sort of device connected to power end results. While powering on along with off, zero-cross of Air Conditioner signal is detected to figure out phase modification. The sensible meter provides appropriate power usage in addition to transfer’s details with WIFI to COMPUTER (Personal Computer). The private checks the power information as well as likewise from one more place manages the system. Normal 0 false false false EN-IN X-NONE TE MicrosoftInternetExplorer4
Narrated for the sake of it: Narration and its Modernist Consonance in T. S. Eliot’s "The Waste Land"

T.S. Eliot’s The Waste Land has received critical acclaim as an anthem of the postwar generation, helping to shape the reception of modernist culture (Gillies & Mahood 2007). Only few critics take a look at its transgeneric character but none has so far looked at how the poem’s narrations pervade modernist tendencies and ideologies of its time. In fact, dubbing it as a variegated or collage poem blatantly dismisses any attempt to include it in the nascent field of narrative poetry. However, on the grounds that it is a typically modernist alternative to continuous narrative and quasi-narrative sequences (McHale 2007) and as a number of its parts are narrated, this essay approaches it from a narratological perspective. The analysis aims to show that those narrations are consonant with and epitomize modernist tendencies and ideologies, including the cyclical view of life and cultural pessimism, the epistemological dominant, skepticism about what we know and how we know it, as well as gender and sexuality issues such as women’s objectification and procreation as the main and most important role of a woman. Key Words: Narrative sequences, collage poem, Narratology, The Waste Land
Schmerzhafte Ansatzanomalie des M. palmaris longus bei einem Konzert-Cellisten

A professional cellist suffered four years from pain and fatigue of unknown etiology to his right thumb while playing his cello. These complaints in his performing right hand were potentially threatening his future career, since he was no longer able to play his instrument. Finally, the diagnosis of an anomaly of the insertion of the palmaris longus tendon was made. After resection of the distal portion of this tendon, the patient's symptoms fully resolved. Anatomic anomalies of the upper limb and particularly of the palmaris longus muscle-tendon unit are frequent and may lead to serious complaints in certain professional groups.
The Ellipsoid Method: A Survey

IN February 1979 a note by L.G. Khachiyan indicated how an ellipsoid method for linear programming can be implemented in polynomial time. This result has caused great excitement and stimulated a flood of technical papers. Ordinarily there would be no need for a survey of work so recent. The current circumstances are obviously exceptional. Word of Khachiyan''s result has spread extraordinarily fast, much faster than comprehension of its significance. A variety of issues have in general not been well understood, including the exact character of the ellipsoid method and of Khachiyan''s result on polynomiality, its practical significance in linear programming, its implementation, its potential applicability to problems outside of the domain of linear programming, and its relationship to earlier work. Our aim here is to help clarify these important issues in the context of a survey of the ellipsoid method, its historical antecedents, recent developments, and current research.
Characterisation of the nicotinic acetylcholine receptor from Manduca sexta.

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Multitask learning on monocular water images: Surface reconstruction and image synthesis

In this paper, we present a new strategy, a joint deep learning architecture, for two classic tasks in computer graphics: water surface reconstruction and water image synthesis. Modeling water surfaces from single images can be regarded as the inverse of image rendering, which converts surface geometries into photorealistic images. On the basis of this fact, we therefore consider these two problems as a cycle image‐to‐image translation and propose to tackle them together using a pair of neural networks, with the three‐dimensional surface geometries being represented as two‐dimensional surface normal maps. Furthermore, we also estimate the imaging parameters from the existing water images with a subnetwork to reuse the lighting conditions when synthesizing new images. Experiments demonstrate that our method achieves an accurate reconstruction of surfaces from monocular images efficiently and produces visually plausible new images under variable lighting conditions.
It's LiFe!: A Monitoring- and Feedback Tool to Stimulate Physical Activity, Embedded in Primary Care

Physical activity improves the long-term prognosis and quality of life of people with a chronic disease like COPD or type 2 diabetes. Therefore, care standards state that stimulating physical activity is a central element in the treatment of those patients in primary care [1,2]. Although there are many initiatives to increase the level of physical activity, few patients manage to be sufficiently active. This may be because care standards also state that the practice nurses and/or GPs see these patients only one to four times a year. Consequently, the level of success regarding this element depends for the greater part on the degree in which patients succeed to execute their self-management role. Therefore, primary care providers should involve patients in self-management decisions and seek together with the patient for lifestyle interventions that fit with the motivation, needs and capabilities of the patient [3,4]. In addition to the support of the care provider, persuasive technology might play an important role in accomplishing the behaviour change, adherence to the new behaviour and the selfmanagement role. A big advantage of persuasion by technology over human persuasion is that technology is more persistent and can go where humans cannot [5]. Through this, personalised feedback can be given on individual performance in relation to goal setting. Self-monitoring of physical activity using a pedometer or an accelerometer has been identified as an effective approach towards behaviour change [6,7]. If embedded in primary care, the combination of human persuasion and persuasive technology could complement and reinforce each other, especially when the two are aligned carefully. In the current project It’s LiFe! an innovative monitoringand feedback tool is being developed and tested, which will be embedded in a Self-management Support Program that is being developed together with this technology. As a prerequisite for useful technology and a successful intervention that meets the requirements and preferences of the end-users, it is important to involve the end users in the design process at an early stage.
Malicious Traffic Detection Using K-means

Various network attacks such as DDoS(Distributed Denial of service) and orm are one of the biggest problems in the modern society. These attacks reduce the quality of internet service and caused the cyber crime. To solve the above problem, signature based IDS(Intrusion Detection System) has been developed by network vendors. It has a high detection rate by using database of previous attack signatures or known malicious traffic pattern. However, signature based IDS have the fatal weakness that the new types of attacks can not be detected. The reason is signature depend on previous attack signatures. In this paper, we propose a k-means clustering based malicious traffic detection method to complement the problem of signature IDS. In order to demonstrate efficiency of the proposed method, we apply the bayesian theorem.