Miracle-dz/UniFAR-FTUs huggingface dataset:
Epistasis between Beneficial Mutations and the Phenotype-to-Fitness Map for a ssDNA Virus

Epistatic interactions between genes and individual mutations are major determinants of the evolutionary properties of genetic systems and have therefore been well documented, but few quantitative data exist on epistatic interactions between beneficial mutations, presumably because such mutations are so much rarer than deleterious ones. We explored epistasis for beneficial mutations by constructing genotypes with pairs of mutations that had been previously identified as beneficial to the ssDNA bacteriophage ID11 and by measuring the effects of these mutations alone and in combination. We constructed 18 of the 36 possible double mutants for the nine available beneficial mutations. We found that epistatic interactions between beneficial mutations were all antagonistic—the effects of the double mutations were less than the sums of the effects of their component single mutations. We found a number of cases of decompensatory interactions, an extreme form of antagonistic epistasis in which the second mutation is actually deleterious in the presence of the first. In the vast majority of cases, recombination uniting two beneficial mutations into the same genome would not be favored by selection, as the recombinant could not outcompete its constituent single mutations. In an attempt to understand these results, we developed a simple model in which the phenotypic effects of mutations are completely additive and epistatic interactions arise as a result of the form of the phenotype-to-fitness mapping. We found that a model with an intermediate phenotypic optimum and additive phenotypic effects provided a good explanation for our data and the observed patterns of epistatic interactions.
Üniversite Öğrencilerinde Fiziksel Aktivite Düzeyi İle Depresyon ve Anksiyete İlişkisi

Bu arastirmanin amaci universite ogrencilerinde fiziksel aktivite duzeyi ile depresyon ve anksiyete iliskisini arastirmakti. Arastirmaya gonullu yas ortalamasi 20,69±1,96 olan 202 erkek ve 253 kiz ogrenci olmak uzere toplamda 455 kisi katilmistir. Arastirmanin fiziksel aktivite degiskeniyle ilgili veriler “Uluslararasi Fiziksel Aktivite Anketi Uzun Formu (UFAA Uzun Form - International Physical Activity Questionnaire)” ile Depresyon degiskeni ile ilgili veriler “Beck Depresyon Envanteri” ile ve anksiyete degiskeniyle ilgili veriler de “Beck Anksiyete Envanteri” ile toplanmistir.Yapilan istatiksel analizler sonucunda erkek ogrencilerin %51,5’in, kiz ogrencilerinde %73,4’un aktif olmadigi veya yetersiz aktivite duzeyine sahip oldugu ve erkek ogrencilerin fiziksel aktivite duzeyinin kiz ogrencilerden anlamli olarak daha yuksek oldugu bulunmustur (Bagimsiz T-testi; p 0,05) ve fiziksel aktivite siniflamasi acisindan cinsiyetler arasinda anlamli bir fark yoktur (Tek Yonlu ANOVA; p>0,05). Ayrica kiz ogrencilerde fiziksel aktivite ile depresyon ve anksiyete arasinda da pozitif yonlu dusuk duzeyde anlamli bir iliski (Pearson korelasyon; p<0,05) bulunmustur. Sonuc olarak universite ogrencilerinde fiziksel aktivite duzeyinin oldukca dusuk oldugu ve ozellikle kiz ogrencilerde fiziksel aktivite puanlari artikca depresyon puanlarinin da artigi soylenebilir.
Phase retrieval without small-ball probability assumptions: Recovery guarantees for phaselift

We study the problem of recovering an unknown vector x ε R<sup>n</sup> from measurements of the form y<sub>i</sub> = |a<sup>T</sup><sub>i</sub> x|<sup>2</sup> (for i = 1,., m), where the vectors a<sub>i</sub> ε R<sup>n</sup> are chosen independently at random, with each coordinate a<sub>ij</sub> ε R being chosen independently from a fixed sub-Gaussian distribution D. However, without making additional assumptions on the random variables a<sub>ij</sub> - for example on the behavior of their small ball probabilities - it may happen some vectors x cannot be uniquely recovered. We show that for any sub-Gaussian distribution V, with no additional assumptions, it is still possible to recover most vectors x. More precisely, one can recover those vectors x that are not too peaky in the sense that at most a constant fraction of their mass is concentrated on any one coordinate. The recovery guarantees in this paper are for the PhaseLift algorithm, a tractable convex program based on a matrix formulation of the problem. We prove uniform recovery of all not too peaky vectors from m = 0(n) measurements, in the presence of noise. This extends previous work on PhaseLift by Candès and Li [8].
Automatic Detection of Lung Nodules in Temporal Subtraction Image by Use of Shape and Density Features

Computer aided diagnosis is one of the most important tools for supporting system on visual screening in medical fields. However, sensitivity for detection of small nodules is unsatisfactory. It is because detection of subtle lesions on computed tomography (CT) images is a difficult task for radiologists. Recently as one of solutions to avoid the problem, a temporal subtraction technique is introduced. The temporal subtraction image is obtained by subtraction of a previous image from a current one, and can be used for enhancing interval changes on medical images by removing most of the normal background structures. In this study, we have developed a new method for automatic detection of lung nodules based on artificial neural networks from a temporal subtraction image. First, the candidates for nodules were detected by use of a multiple threshold technique based on the pixel value in the temporal subtraction images obtained by the voxel-matching technique. Next, false positives of nodules candidate are removed by use of selective enhancement filter and a rule-based method with classifier based on artificial neural networks. We applied our computerized scheme to 6 MDCT cases including 87 lung nodules. Our scheme for detecting lung nodules provided a sensitivity of 80.5% for lung nodules with sizes less than 20mm, and with 7.5 false positives per scan. In this paper, we discussed the experimental result of detection and statistical features.
Soundcomber: A Stealthy and Context-Aware Sound Trojan for Smartphones

We explore the threat of smartphone malware with access to on-board sensors, which opens new avenues for illicit collection of private information. While existing work shows that such “sensory malware” can convey raw sensor data (e.g., video and audio) to a remote server, these approaches lack stealthiness, incur significant communication and computation overhead during data transmission and processing, and can easily be defeated by existing protections like denying installation of applications with access to both sensitive sensors and the network. We present Soundcomber, a Trojan with few and innocuous permissions, that can extract a small amount of targeted private information from the audio sensor of the phone. Using targeted profiles for context-aware analysis, Soundcomber intelligently “pulls out” sensitive data such as credit card and PIN numbers from both toneand speech-based interaction with phone menu systems. Soundcomber performs efficient, stealthy local extraction, thereby greatly reducing the communication cost for delivering stolen data. Soundcomber automatically infers the destination phone number by analyzing audio, circumvents known security defenses, and conveys information remotely without direct network access. We also design and implement a defensive architecture that foils Soundcomber, identify new covert channels specific to smartphones, and provide a video demonstration
Analytic Comparison of Three Methods to Evaluate Tutorial Behaviors

We compare the purposes, inputs, representations, and assumptions of three methods to evaluate the fine-grained interactions of intelligent tutors with their students. One method is conventional analysis of randomized controlled trials (RCTs). The second method is learning decomposition, which estimates the impact of each practice type as a parameter in an exponential learning curve. The third method is knowledge tracing, which estimates the impact of practice as a probability in a dynamic Bayes net. The comparison leads to a generalization of learning decomposition to account for slips and guesses.
Sequential Quadratic Programming Based on IPM for Constrained Nonlinear Programming

The field of constrained nonlinear programming (NLP) has been principally challenging to various gradient based optimization techniques. The sequential quadratic programming algorithm (SQP) that uses active set strategy in solving quadratic programming (QP) subproblems proves to be efficient in locating the points of local optima. However, its efficient determination of the optimal active set heavily relies on the initial guess of the starting point. This remains a serious drawback to both primal and dual active set approaches especially for NLPs with several inequality constraints. Thus, we propose a sequential quadratic programming algorithm (SQP/IPM) which uses an infeasible interior point method (IIPM) for the determination of descent directions. We propose using quadratic search algorithm for effective minimization of merit functions. Our test results reveal that SQP/IPM algorithm is efficient and promising.
WCET-driven Cache-based Procedure Positioning Optimizations

Procedure Positioning is a well known compiler optimization aiming at the improvement of the instruction cache behavior. A contiguous mapping of procedures calling each other frequently in the memory avoids overlapping of cache lines and thus decreases the number of cache conflict misses. In standard literature, these positioning techniques are guided by execution profile data and focus on an improved average-case performance. We present two novel positioning optimizations driven by worst-case execution time (WCET) information to effectively minimize the program's worst-case behavior. WCET reductions by 10% on average are achieved. Moreover, a combination of positioning and the WCET-driven Procedure Cloning optimization proposed in [14] is presented improving the WCET analysis by 36% on average.
Visual speech analysis and synthesis with application to Mandarin speech training

This paper presents a novel vision-based speech analysis system STODE which is used in spoken Chinese training of oral deaf children. Its design goal is to help oral deaf children overcome two major difficulties in speech learning: the confusion of intonations for spoken Chinese characters and timing errors within different words and characters. It integrates such capabilities as real-time lip tracking and feature extraction, multi-state lip modeling, Time-delay Neural Network (TDNN) for visual speech analysis. A desk-mounted camera tracks users in real-time. At each frame, region of interest is identified and key information is extracted. The preprocessed acoustic and visual information are then fed into a modular TDNN and combined for visual speech analysis. Confusion of intonations for spoken Chinese characters can be easily identified, and timing error within words and characters also can be detected using a DTW (Dynamic Time Warping) algorithm. For visual feedback we have created an artificial talking head directly cloned from user's own images to generate correct outputs showing both correct and wrong ways of pronunciation. This system has been successfully used for spoken Chinese training of oral deaf children in cooperation with Nanjing Oral School under grants from National Natural Science Foundation of China.
Institutional Mechanisms of Spatial Development Challenged by Global Processes

This report introduces a Nordic research programme focusing on future challenges and institutional preconditions for regional development policy. These challenges will have to be faced in an environment marked by globalisation, with its major features reflected in the economy, society, means of communication and information management. There is also a whole a set of old and new hazards, which will have to be handled through the modes of ecological mod-ernisation chosen by our societies. The developments set forth in this volume's four broad essays (Chapters 2-4) have been produced by Nordic scientists who have dared proceed beyond the limits of standard academic discussion. This common venture involved drafting visions for the Nordic societies as they could appear within the next fifteen years or so – or at least expose some partly foreseeable, partly barely conceivable , and partly undesirable images of that future. While studying the images still looming outside of the range of our clear vision we must endeavour to keep in mind the fact that the mirror-world of scenarios reflects possible futures, not the future. Determine what is a wanted or an unwanted vision of what may lie ahead of us is, first of all, a question of our own preferences and valuations. There are few things that can be labelled as absolutely good or absolutely bad. Furthermore, even in the rare cases where this is so, just what actions are needed to either make them come true or avoid them at any price may be anything but clear to us. Even if we embark well armed with facts, we may be totally unfamiliar with the dynamics taking place within those black boxes beyond our grasp. What really counts is the combination and interplay of two main elements, the facts (structural elements) and the process. To make the situation even more complex, one could well argue that the process – the trickier of the two elements not least because it allows for practically infinite combinations of the facts – is obviously the most decisive one.
Whatsapp Addiction Affecting Students at Politeknik Sultan Mizan Zainal Abidin

Nowadays, surfing the internet across virtual borders became a must to almost every layer of society. The existence of various social sites like Facebook, Twitter, Instagram and WhatsApp as medium to communicate became widely used because the internet is accessible to anyone regardless of place and time. Excessive use of WhatsApp is addictive and it gave different impact in terms of advantages and disadvantages to the users. Highlights from this, this paper work was done to assess the influence of the excessive use of WhatsApp on the attitude of students of PSMZA. A total of 250 students were randomly selected which consists of male and female students. The methodology used is descriptive method and quantitative approach that is using the questionnaire instrument consisting of three parts, namely part A respondent's demographic information, part B of the information level of addiction to the use of WhatsApp and part C information relating to the attitude of students either positive or negative towards their environment. The data collected is processed through the software IBM SPSS Statistics version 23. From the study it was found that the influence of the use of excessive WhatsApp still had positive impact on the attitudes of students of PSMZA. However, female students were more addicted to WhatsApp compared to male students.
Extraction of essential oils from lime (Citrus latifolia Tanaka) by hydrodistillation and supercritical carbon dioxide

Neste trabalho o oleo essencial de lima acida foi extraido por hidrodestilacao e CO2 supercritico. No caso da hidrodestilacao, os parâmetros avaliados foram o tempo de processo e caracteristicas do material vegetal. Em extracao supercritica, os parâmetros avaliados foram temperatura, pressao e fluxo do CO2, tempo de processo e caracteristicas do material. Considerando o conteudo de citral, os melhores resultados para hidrodestilacao foram obtidos em um tempo de processo de 3 horas utilizando-se cascas inteiras. Os melhores resultados para extracao supercritica foram obtidos a 60oC, 90 bar, a um fluxo de CO2 de 1 mL/ min para 30 minutos de processo utilizando-se cascas moidas. Os melhores resultados em termos de rendimento de oleo essencial foram obtidos por hidrodestilacao (5,45% p/p) e extracao supercritica (7,93% p/p), para cascas moidas.
PeRCeIVE: Proactive caching in ICN-based VANETs

The networking of components, machines and everyday objects is progressing rapidly. This development also affects the automotive industry. Vehicle systems are getting connected with other cars, infrastructure components or cloud servers. This raises the question if the current host-centric communication model of today's networks is ready for networking billions of new devices. The Information-Centric Networking (ICN) paradigm is a promising candidate to solve the issues set by connected vehicles and host-centric communication, for example by providing in-network caching capabilities. However, placing the right content at the right node in-time is a non trivial task. Within this paper, we introduce PeRCeIVE, a PRoactive Caching approach for Icn-based Vehicular ad-hoc nEtworks (VANETs). PeRCeIVE shows that a directed placement of data will improve the performance of the network by distributing the content with a minimal number of replicas one-hop away from the consumer.
A Reservation-Based CSMA Protocol for Integrated Manufacturing Networks

This paper presents PCSMA, an extension to the CSMA/CD protocol (used in the Ethernet) to support both conventional datagram traffic and real-time traffic. The protocol provides predictable packet-delivery bounds for real-time traffic. It does not require changes to existing Ethernet controllers for datagram traffic. Under the new protocol, periodic sources follow a variation of the CSMA protocol that requires them to reserve transmission slots before they can begin transmission. This protocol is intended particularly for use in the integrated network in a manufacturing shop. Periodic sources include multiple sensors generating disparate types and rates of data. We have carried out an extensive performance evaluation of the protocol using a simulation model. The results are impressive: PCSMA shows fewer collisions than CSMA, equivalent delays for conventional traffic, and no failures to meet deadlines for periodic traffic. >
Massive boson‐fermion degeneracy and the early structure of the universe

The existence of a new kind of massive boson‐fermion symmetry is shown explicitly in the framework of the heterotic, type II and type II orientifold superstring theories. The target space‐time is two‐dimensional. Higher dimensional models are defined via large marginal deformations of JJ‐type. The spectrum of the initial undeformed two dimensional vacuum consists of massless boson degrees of freedom, while all massive boson and fermion degrees of freedom exhibit a new Massive Spectrum Degeneracy Symmetry (MSDS). This precise property, distinguishes the MSDS theories from the well known supersymmetric SUSY‐theories. Some proposals are stated in the framework of these theories concerning the structure of: (i) The Early Non‐singular Phase of the Universe, (ii) The two dimensional boundary theory of AdS3 Black‐Holes, (iii) Plausible applications of the MSDS theories in particle physics, alternative to SUSY.
A 60-GHz Power Amplifier Design Using Dual-Radial Symmetric Architecture in 90-nm Low-Power CMOS

An innovative on-chip 3-D power amplifier (PA) architecture for M-way power-combined CMOS PAs by using the proposed dual-radial symmetric architecture is presented. It provides design freedom of impedance selection of power device in transformer-based millimeter-wave PA design. This idea also makes distinguished breakthrough to the traditional 2-D PA architecture without compromising symmetry and compact size of layout. To demonstrate the feasibility of this idea, a 60-GHz PA is fabricated in 90-nm low-power CMOS process. It is also equipped with multi-mode operation. It achieves an output power of 18.5 dBm and a power-added efficiency of 10.2% with 1.2-V supply voltage. At 6-dB/10-dB power back-off operation, the drain efficiencies of power stage can be enhanced from 5.9%/2.4% to 11.9%/8%, respectively, by enabling the multi-mode operation.
Family status and later-life depression among older adults in urban Latin America and the Caribbean

Abstract Rapid fertility declines in Latin American and Caribbean countries since the 1960s have contributed to smaller family sizes among the current cohorts of older adults. This may have mental health implications in these societies as the family unit is highly valued as a source of social support. Utilising data from the 2000 Survey of Health, Well-being and Aging in Latin America and the Caribbean (SABE), this study examines the association between parental status, marital status and the likelihood of experiencing depressive symptoms among adults 60 years and older in seven cities within Latin America and the Caribbean (N = 9,756): Buenos Aires, Bridgetown, São Paulo, Santiago, Havana, Mexico City and Montevideo. Results from multivariate logistic regressions indicate that parental status is not significantly associated with depressive symptoms. Nonetheless, unmarried older adults, both those living alone and those living with others, are more vulnerable to experiencing depressive symptoms than their married counterparts. Marriage is especially protective for older adults in Havana and Montevideo. Older adults’ perceived income adequacy significantly moderates the relationship between marital status and depressive symptoms. Other significant covariates, such as experiencing disability and comorbidity, showed positive associations with depressive symptoms. While families may still represent a critical component for the mental health of older adults, broader investments in health across the lifespan are needed to improve individual psychological wellbeing.
Privacy Preserving Two-Party Hierarchical Clustering Over Vertically Partitioned Dataset

Data mining has been a popular research area for more than a decade. There are several problems associated with data mining. Among them clustering is one of the most interesting problems. However, this problem becomes more challenging when dataset is distributed between different parties and they do not want to share their data. So, in this paper we propose a privacy preserving two party hierarchical clustering algorithm vertically partitioned data set. Each site only learns the final cluster centers, but nothing about the individual’s data.
Slice WIM: a multi-surface, multi-touch interface for overview+detail exploration of volume datasets in virtual reality

We present Slice WIM, a method for overview+detail visualization of volume datasets that explores the potential of new interfaces made possible by a virtual reality (VR) environment made of two display surfaces: an interactive multi-touch table, and a stereoscopic display wall. Slice WIM displays a miniature version of the 3D dataset within a head-tracked stereoscopic view such that it appears to float directly above the multi-touch table. Multi-touch gestures on the table are then used to navigate through the dataset and to set slices (cutting planes) through the data. Leveraging the unique table+wall hardware setup, horizontal slices through the data are projected (like a shadow) down onto the table surface, providing a useful 2D data overview to complement the 3D views as well as a data context for interpreting 2D multi-touch gestures made on the table. We demonstrate several strategies for interacting with 2D "shadow slices" on the table surface as a method for controlling the WIM and exploring volumetric datasets. Applications of the interface to explore two different volume datasets are presented, and design decisions and limitations are discussed along with feedback from both casual users and domain scientists.
A Method for Segmentation of Retinal Image Vessels

Retinal image vessels can reflect different states of many diseases, which are often used for the registration and mosaic of retinal images. Therefore, it is very important to accurately extract blood vessels. The paper firstly analyzes the characteristic of retinal images, and secondly gray mathematical morphology theories are used to smooth and strengthen retinal images in order to remove the background and enhance the brightness of retinal blood vessels, finally retinal blood vessels are extracted with entropy threshold method. Compared to the result segmented by manual of experts, our approach can get more accuracy and lower misclassify ratio