Miracle-dz/UniFAR-FTUs huggingface dataset:
A multi-objective memetic algorithm for relay node placement in wireless sensor network

This paper proposes a multi-objective memetic algorithm, namely Mem-NSGA-II, to optimize the relay node placement problem. The network lifetime and the number of relay nodes are two objectives to be optimized. In Mem-NSGA-II, three new local search (LS) operations are designed and incorporated into the fast non-dominated genetic algorithm II (NSGA-II). The first LS operation inserts relay nodes into solutions for extending the network lifetime. The second LS operation aims to reduce the number of relay nodes to save cost. The third LS operation fine-tunes positions of the relay nodes for finding better solutions. The performance of Mem-NSGA-II is compared with a deterministic two-phased method and NSGA-II. Simulation results on five networks reveal that Mem-NSGA-II yields much better performance than the two algorithms.
MIMO OFDM radar networks: Inter- & intra-system interference handling

In OFDM-based radar-communication systems and networks, the limiting factor of the radar's performance is the inter-system interference. In the case of MIMO OFDM radar systems, the intra-system interference can be mitigated with proper subcarrier assignment to the multiple transmit antennas but inter-system interference cannot be totally avoided. Interfering communication-radar signals appear as Gaussian white noise to the OFDM-based radar system hence conventional filtering methods cannot be used. By exploiting the communication capability of OFDM signals, the payload data can be demodulated then subtracted from the received radar signal to improve the dynamic range of the radar estimation. This paper presents an interference cancellation technique for MIMO OFDM radar systems to counter inter-system interference.
Comment on "The Uniform Alcoholism and Intoxication Treatment Act".

Kurtz and Regier (1) have presented a very thoughtful, important and provocative statement in which they impute to individuals whom they call "alcohologists" various strategies for effecting change in social policy. It is my purpose to suggest that Kurtz and Regier have, in some places, confused the historical order of events and minimized the significance of research findings as they were applied to social strategy and social policy. I will comment particularly on the decade of the 1940s in which the authors suggest hat a movement spearheaded by "alcohologists" was "gradually successful in building a new image of the alcoholism problem via the disease model; it also made gains in dissociating alcoholics from the Skid Row image. " As the authors saw events, the "use of the 'derelict model' of alcoholism seemed dysfunctional to the disease model, necessitating a redefinition of who is to be included in the category of 'alcoholic. '" The authors then suggest that Skid Row alcoholics were differentiated from other alcoholics in
Diagnosing Abnormal Electrocardiogram (ECG) via Deep Learning

In this chapter, we investigate the most recent automatic detecting algorithms on abnormal electrocardiogram (ECG) in a variety of cardiac arrhythmias. We pres-ent typical examples of a medical case study and technical applications related to diagnosing ECG, which include (i) a recently patented data classifier on the basis of deep learning model, (ii) a deep neural network scheme to diagnose variable types of arrhythmia through wearable ECG monitoring devices, and (iii) implementation of the health cloud platform, which consists of automatic detection, data mining, and classifying via the Android terminal module. Our work establishes a cross-area study, which relates artificial intelligence (AI), deep learning, cloud computing on huge amount of data to minishape ECG monitoring devices, and portable interaction platforms. Experimental results display the technical advantages such as saving cost, better reliability, and higher accuracy of deep learning-based models in contrast to conventional schemes on cardiac diagnosis.
IIT (BHU): System Description for LSDSem’17 Shared Task

This paper describes an ensemble system submitted as part of the LSDSem Shared Task 2017 - the Story Cloze Test. The main conclusion from our results is that an approach based on semantic similarity alone may not be enough for this task. We test various approaches and compare them with two ensemble systems. One is based on voting and the other on logistic regression based classifier. Our final system is able to outperform the previous state of the art for the Story Cloze test. Another very interesting observation is the performance of sentiment based approach which works almost as well on its own as our final ensemble system.
Differential Roles of Insulin and IGF-1 Receptors in Adipose Tissue Development and Function

To determine the roles of insulin and insulin-like growth factor 1 (IGF-1) action in adipose tissue, we created mice lacking the insulin receptor (IR), IGF-1 receptor (IGF1R), or both using Cre-recombinase driven by the adiponectin promoter. Mice lacking IGF1R only (F-IGFRKO) had a ∼25% reduction in white adipose tissue (WAT) and brown adipose tissue (BAT), whereas mice lacking both IR and IGF1R (F-IR/IGFRKO) showed an almost complete absence of WAT and BAT. Interestingly, mice lacking only the IR (F-IRKO) had a 95% reduction in WAT, but a paradoxical 50% increase in BAT with accumulation of large unilocular lipid droplets. Both F-IRKO and F-IR/IGFRKO mice were unable to maintain body temperature in the cold and developed severe diabetes, ectopic lipid accumulation in liver and muscle, and pancreatic islet hyperplasia. Leptin treatment normalized blood glucose levels in both groups. Glucose levels also improved spontaneously by 1 year of age, despite sustained lipodystrophy and insulin resistance. Thus, loss of IR is sufficient to disrupt white fat formation, but not brown fat formation and/or maintenance, although it is required for normal BAT function and temperature homeostasis. IGF1R has only a modest contribution to both WAT and BAT formation and function.
Building product-lines of mixed-criticality systems

Mixed-Criticality Systems (MCS) reconcile safetycritical requirements with multi-core architectures, by offering spatial and temporal isolation while preserving other extrafunctional properties such as optimised energy consumption or minimised latencies. MCS designers struggle to manually balance the offered functionalities with pertinent implementation choices in order to ensure that the system eventually meets all constraints. Existing attempts to further automate this process focus on specific concerns, and fail to account for variation in system functionalities. Our contribution is to integrate product-lines that capture functional variations with evolutionary optimisation to explore possible implementations and their impact on extrafunctional properties. Our solution is a model-driven process (and a tool prototype) to automatically select functionally different products that balance well the various concerns of interest. We illustrate how this process applies to the construction of wind turbines. Moving toward product-lines eventually contributes to reduce high development costs and the long time to market associated with MCS.
Winner of the 2008 Systematic Review Competition: Knee Osteoarthritis after Anterior Cruciate Ligament Injury

Background This is a systematic review of studies on the prevalence of osteoarthritis in the tibiofemoral joint more than 10 years after an anterior cruciate ligament injury, the radiologic classification methods used, and risk factors for development of knee osteoarthritis. Methods A systematic search was performed in PubMed, EMBASE, and AMED. Inclusion criteria were studies involving patients with anterior cruciate ligament injury, either isolated or combined with medial collateral ligament or meniscal injury and either surgically or nonsurgically treated, and a minimum 10-year follow-up with radiologic assessment. Methodological quality was evaluated using a modified version of the Coleman methodology score. Results Seven prospective and 24 retrospective studies were included. The mean modified Coleman methodology score was 52 of 90. Reported prevalence of knee osteoarthritis for subjects with isolated anterior cruciate ligament injury was between 0% and 13%. For subjects with anterior cruciate ligament and additional meniscal injury, the prevalence varied between 21% and 48%. Seven different radiologic classification systems were used in the studies. Only 3 studies reported reliability results for the radiologic assessments. The most frequently reported risk factor for development of knee osteoarthritis was meniscal injury. Conclusion This systematic review suggests that the prevalence rates of knee osteoarthritis after anterior cruciate ligament reconstruction reported by previous reviews have been too high. The highest rated studies reported low prevalence of knee osteoarthritis for individuals with isolated anterior cruciate ligament injury (0%-13%) and a higher prevalence of knee osteoarthritis for subjects with combined injuries (21%-48%). Overall, the modified Coleman methodology score was low for the included studies. No universal methodological radiologic classification method exists, making comparisons of the studies and stating firm conclusions on the prevalence of knee osteoarthritis more than 10 years after anterior cruciate ligament injury difficult.
Obstetric Sepsis: Focus on the 3-Hour Bundle

Early recognition and treatment of sepsis are key to decreasing maternal and fetal morbidity and mortality. Timing is critical, and early intervention is associated with improved outcomes. The perinatal provider is in a unique position to identify risk factors, perform assessments, and implement the first 3 hours of the sepsis bundle. Early detection and management combined with careful assessment can assist in providing evidence-based care and moving the patient to a higher level of care when warranted.
A Novel Scaling Free Vectoring CORDIC and its FPGA Implementation

This research paper proposes a novel scaling free CORDIC algorithm to operate in vectoring mode which computes absolute magnitude and phase angle of input vector. Using this algorithm, the micro rotation of the vector is unidirectional and totally scaling free. The range of convergence is successfully extended to cover entire coordinate space without increasing any hardware complexity.Further a 16 bit Scaling free vectoring CORDIC architecture based on this proposed algorithm is synthesized on FPGA Xilinx Virtex-5 device using Verilog hardware description language. Synthesized results show throughput every clock cycle with maximum operating frequency of 243.55MHz and demonstrate very low dynamic power consumption.
A multilevel synergy Thompson sampling hyper-heuristic for solving Max-SAT

Hyper-heuristics are high-level methods, used to solve various optimization problems. Some of them are capable of learning and adapting their behavior throughout the solving process. Selection hyper-heuristics evaluate low-level heuristics and determine which of them to be applied at a given point in the search process. However, it has been shown that the additive learning process becomes inefﬁcient in hard problems where the probability of ﬁtness improvement is less than 12 . Other alternative learning mechanisms have been proposed however they don’t take into account the synergy between the low-level heuristics. Moreover they haven’t been tested on large NP-hard problems. In this work, we propose a new hyper-heuristic which we called the Multilevel Synergy Thompson Sampling Hyper-Heuristic . The proposed method includes both the probabilistic learning mechanism and the multilevel paradigm. The latter refers to the process of creating hierarchically smaller sub-problems from large problem instances. The proposed hyper-heuristic is applied on very large industrial Max-SAT instances from the latest Max-SAT competition. The numerical results are promising and demonstrate the beneﬁts of our method. The proposed method outperforms the other four types of hyper-heuristics: Random, Choice Function, Stochastic Choice Function and the simple Thompson Sampling Hyper-Heuristics.
Emotional Social Signals for Search Ranking

A large amount of social feedback expressed by social signals (e.g. like, +1, rating) are assigned to web resources. These signals are often exploited as additional sources of evidence in search engines. Our objective in this paper is to study the impact of the new social signals, called Facebook reactions (love, haha, angry, wow, sad) in the retrieval. These reactions allow users to express more nuanced emotions compared to classic signals (e.g. like, share). First, we analyze these reactions and show how users use these signals to interact with posts. Second, we evaluate the impact of each such reaction in the retrieval, by comparing them to both the textual model without social features and the first classical signal (like-based model). These social features are modeled as document prior and are integrated into a language model. We conducted a series of experiments on IMDb dataset. Our findings reveal that incorporating social features is a promising approach for improving the retrieval ranking performance.
A model-based approach to predict muscle synergies using optimization: application to feedback control

This paper presents a new model-based method to define muscle synergies. Unlike the conventional factorization approach, which extracts synergies from electromyographic data, the proposed method employs a biomechanical model and formally defines the synergies as the solution of an optimal control problem. As a result, the number of required synergies is directly related to the dimensions of the operational space. The estimated synergies are posture-dependent, which correlate well with the results of standard factorization methods. Two examples are used to showcase this method: a two-dimensional forearm model, and a three-dimensional driver arm model. It has been shown here that the synergies need to be task-specific (i.e., they are defined for the specific operational spaces: the elbow angle and the steering wheel angle in the two systems). This functional definition of synergies results in a low-dimensional control space, in which every force in the operational space is accurately created by a unique combination of synergies. As such, there is no need for extra criteria (e.g., minimizing effort) in the process of motion control. This approach is motivated by the need for fast and bio-plausible feedback control of musculoskeletal systems, and can have important implications in engineering, motor control, and biomechanics.
Awareness of cancer risk factors among patients and attendants presenting to a tertiary care hospital in Karachi, Pakistan.

OBJECTIVE To determine awareness of cancer risk factors in the patients and attendants of Out-patient Clinics at a University Hospital in Karachi, Pakistan. METHODS A cross-sectional survey was conducted on 315 respondents reporting to a tertiary care hospital in Karachi, Pakistan, to assess their level of awareness regarding risk factors of cancer. RESULTS The respondents belonged to an urban population with the mean time spent in Karachi of 29.1 years (SD +/- 13.94). There were 213 (67%) males and 102 (33%) females. All respondents had heard of the word 'cancer', while only 57.5% were aware of cancer risk factors. However, only 42.8% could identify age, 33% diet, 35% drugs and 31% obesity as risk factors for cancer. Even those who were aware of the risk factors were not able to appreciate personal risk of cancer. CONCLUSION Despite awareness regarding some of the risk factors, the surveyed population was not aware of intrinsic risk factors for cancers like increasing age and obesity. It is important to create awareness through educational programs on cancer prevention, dissemination of knowledge pertaining to the preventable and avoidable cancer risk factors, the benefits of early diagnosis, and availability of screening tests.
Hypothalamic Gene Expression in Sheep for Cocaine- and Amphetamine-Regulated Transcript, Pro-Opiomelanocortin, Neuropeptide Y, Agouti-Related Peptide and Leptin Receptor and Responses to Negative Energy Balance

Hypothalamic pathways involved in the regulation of energy balance have not been widely studied in ruminants to date. Here, we used in situ hybridisation to study the gene expression of a number of leptin-sensitive receptors and neuropeptides in the ovine hypothalamus. Gene expression was first localised for cocaine- and amphetamine-regulated transcript (CART) and agouti-related peptide (AGRP). We then examined in adult male castrated sheep the effects of acute negative energy balance induced by a 4-day fast on the amounts of these mRNAs and those for leptin receptor (OB-Rb), neuropeptide Y (NPY) and pro-opiomelanocortin (POMC). CART mRNA was localised in the arcuate nucleus (ARC), paraventricular nucleus, median eminence and ventromedial hypothalamic nucleus, and extensive co-localisation with POMC mRNA was demonstrated in the ARC. AGRP mRNA was localised in the ARC. Fasting up-regulated gene expression for OB-Rb and for the orexigenic neuropeptides NPY and AGRP in the ARC. There was a trend towards down-regulation of gene expression for the anorexigenic neuropeptide CART and no effect on POMC in the ARC, although these results are inconclusive. The presence or absence of oestradiol-containing subcutaneous implants did not influence gene expression or the effects of fasting. The hypothalamic changes were consistent with responses to the observed reduction in circulation leptin and suggest that the peripheral feedback and central mechanisms for restoring the energy balance may be largely conserved across monogastric and ruminant species.
W32.Duqu: The Precursor to the Next Stuxnet

On October 14, 2011, we were alerted to a sample by the Laboratory of Cryptography and System Security (CrySyS) at Budapest University of Technology and Economics. The threat appeared very similar to the Stuxnet worm from June of 2010 [1]. CrySyS named the threat Duqu [dyu-kyu] because it creates files with the file name prefix “~DQ” [2]. We confirmed Duqu is a threat nearly identical to Stuxnet, but with a completely different purpose of espionage rather than sabotage.
Atherosclerosis in Japanese Youth with Reference to Differences between Each Artery a

Various diseases caused by arterial atherosclerosis are generally considered to be clinically geriatric diseases, but arterial lesions recognizable as early changes of atherosclerosis, such as fatty streaks, may often be seen in the arteries of young people. If one thinks that such arterial changes in youth may be early lesions, which may be expected to progress to more advanced atherosclerosis decades later, a clinically latent period should be very long. ’ Thus, precise investigations of arteries in youth seem to be very important in order to make clear what the initial factors in atherosclerosis are and how early lesions progress to more advanced ones in humans, playing an important role later in developing ischemic diseases in various organs in people past middle age. As part of a multiinstitutional cooperative study of atherosclerosis in infants, children, and young adults in Japan (group director: Dr. Kenzo Tanaka, Kyushu University, Fukuoka),’ the present study pays special attention to the differences between each artery, particularly between aortae and coronary arteries.
Multilingwis – A Multilingual Search Tool for Multi-Word Units in Multiparallel Corpora

We describe a web-based application for searching translations of multi-word units in large, openly available multiparallel corpora. This web application offers a unique resource for multilingual terminologists and translators. The first edition of the tool covers the debates of the European Parliament in five languages: English, French, German, Italian, and Spanish. Our search tool provides a simple and intuitive user interface, which optimally supports content-oriented queries while relieving the user from specifying complicated search expressions in a complex query language. We describe the necessary automatic preprocessing steps of the linguistic data, the retrieval component, and the techniques needed for offering a zero configuration search.
DNN Training Based on Classic Gain Function for Single-channel Speech Enhancement and Recognition

For conventional single-channel speech enhancement based on noise power spectrum, the speech gain function, which suppresses background noise at each time-frequency bin, is calculated by prior signal-to-noise-ratio (SNR). Hence, accurate prior SNR estimation is paramount for successful noise suppression. Accordingly, we have proposed a single-channel approach to combine conventional and deep learning techniques for speech enhancement and automatic speech recognition (ASR) recently. However, the combination process is at the testing stage, which is time-consuming with a complicated procedure. In this study, the gain function of classic speech enhancement will be utilized to optimize the ideal ratio mask based deep neural network (DNN-IRM) at the training stage, denoted as GF-DNN-IRM. And at the testing stage, the estimated IRM by GF-DNN-IRM model is directly used to generate enhanced speech without involving the conventional speech enhancement process. In addition, DNNs with less parameters in the causal processing mode are also discussed. Experiments of the CHiME-4 challenge task show that our proposed algorithm can achieve a relative word error rate reduction of 6.57% on RealData test set comparing to unprocessed speech without acoustic model retraining in causal mode, while the traditional DNN-IRM method fails to improve ASR performance in this case.
Overlapping factors in search engine optimization and web accessibility

Purpose – The purpose of this paper is to show that the pursuit of a high search engine relevance ranking for a webpage is not necessarily incompatible with the pursuit of web accessibility.Design/methodology/approach – The research described arose from an investigation into the observed phenomenon that pages from accessible websites regularly appear near the top of search engine (such as Google) results, without any deliberate effort having been made through the application of search engine optimization (SEO) techniques to achieve this. The reasons for this phenomenon appear to be found in the numerous similarities and overlapping characteristics between SEO factors and web accessibility guidelines. Context is provided through a review of sources including accessibility standards and relevant SEO studies and the relationship between SEO and web accessibility is described. The particular overlapping factors between the two are identified and the precise nature of the overlaps is explained in greater detai.