Miracle-dz/UniFAR-FTUs huggingface dataset:
Compromising Electromagnetic Emanations of Wired and Wireless Keyboards

Computer keyboards are often used to transmit confidential data such as passwords. Since they contain electronic components, keyboards eventually emit electromagnetic waves. These emanations could reveal sensitive information such as keystrokes. The technique generally used to detect compromising emanations is based on a wide-band receiver, tuned on a specific frequency. However, this method may not be optimal since a significant amount of information is lost during the signal acquisition. Our approach is to acquire the raw signal directly from the antenna and to process the entire captured electromagnetic spectrum. Thanks to this method, we detected four different kinds of compromising electromagnetic emanations generated by wired and wireless keyboards. These emissions lead to a full or a partial recovery of the keystrokes. We implemented these sidechannel attacks and our best practical attack fully recovered 95% of the keystrokes of a PS/2 keyboard at a distance up to 20 meters, even through walls. We tested 12 different keyboard models bought between 2001 and 2008 (PS/2, USB, wireless and laptop). They are all vulnerable to at least one of the four attacks. We conclude that most of modern computer keyboards generate compromising emanations (mainly because of the manufacturer cost pressures in the design). Hence, they are not safe to transmit confidential information.
The Imaginary Part of Coherency in Autism: Differences in Cortical Functional Connectivity in Preschool Children

Cognition arises from the transient integration and segregation of activity across functionally distinct brain areas. Autism Spectrum Disorders (ASD), which encompass a wide range of developmental disabilities, have been presumed to be associated with a problem in cortical and sub-cortical dynamics of coordinated activity, often involving enhanced local but decreased long range coordination over areas of integration. In this paper we challenge this idea by presenting results from a relatively large population of ASD children and age-matched controls during a face-processing task. Over most of the explored domain, children with ASD exhibited enhanced synchronization, although finer detail reveals specific enhancement/reduction of synchrony depending on time, frequency and brain site. Our results are derived from the use of the imaginary part of coherency, a measure which is not susceptible to volume conduction artifacts and therefore presents a credible picture of coordinated brain activity. We also present evidence that this measure is a good candidate to provide features in building a classifier to be used as a potential biomarker for autism.
Invited review: Body condition score and its association with dairy cow productivity, health, and welfare.

The body condition score (BCS) of a dairy cow is an assessment of the proportion of body fat that it possesses, and it is recognized by animal scientists and producers as being an important factor in dairy cattle management. The scale used to measure BCS differs between countries, but low values always reflect emaciation and high values equate to obesity. The intercalving profile of BCS is a mirror image of the milk lactation profile. Cows lose condition for 50 to 100 d postcalving, because of homeorhetic changes that occur in the somatotropic axis and the sensitivity of peripheral tissues to insulin, and the upregulation of lipolytic pathways in adipose tissue. Management and feeding have little effect on early postcalving BCS loss (wk 1 to 4 postcalving) until the natural period of insulin resistance has passed and the somatotropic axis has recoupled. There is evidence, however, that management and diet can influence the timing of recoupling of the somatotropic axis and the sensitivity of peripheral tissues to insulin, and gene expression differences in adipose tissue 30 d in milk confirm an effect of energy intake on lipogenic enzymes. The BCS in which a cow calves, nadir BCS, and the amount of BCS she loses postcalving are associated with milk production, reproduction, and health. Body condition score may also be a valid indicator of animal welfare, but further research is required to determine the effect of BCS and BCS change on how a cow "feels. " Although the actual strength of the association may vary, there is relative consistency in the associations among calving and nadir BCS, and BCS change on milk production, postpartum anestrous, the likelihood of a successful pregnancy and days open, the risk of uterine infection, and the risk of metabolic disorders. For many production and health variables, the association with BCS is nonlinear, with an optimum calving BCS of 3.0 to 3.25 (5-point scale); lower calving BCS is associated with reduced production and reproduction, whereas calving BCS >/=3.5 (5-point scale) is associated with a reduction in early lactation dry matter intake and milk production and an increased risk of metabolic disorders. Ongoing research into the automation of body condition scoring suggests that it is a likely candidate to be incorporated into decision support systems in the near future to aid producers in making operational and tactical decisions.
Chunking dynamics: heteroclinics in mind

Recent results of imaging technologies and non-linear dynamics make possible to relate the structure and dynamics of functional brain networks to different mental tasks and to build theoretical models for the description and prediction of cognitive activity. Such models are non-linear dynamical descriptions of the interaction of the core components—brain modes—participating in a specific mental function. The dynamical images of different mental processes depend on their temporal features. The dynamics of many cognitive functions are transient. They are often observed as a chain of sequentially changing metastable states. A stable heteroclinic channel (SHC) consisting of a chain of saddles—metastable states—connected by unstable separatrices is a mathematical image for robust transients. In this paper we focus on hierarchical chunking dynamics that can represent several forms of transient cognitive activity. Chunking is a dynamical phenomenon that nature uses to perform information processing of long sequences by dividing them in shorter information items. Chunking, for example, makes more efficient the use of short-term memory by breaking up long strings of information (like in language where one can see the separation of a novel on chapters, paragraphs, sentences, and finally words). Chunking is important in many processes of perception, learning, and cognition in humans and animals. Based on anatomical information about the hierarchical organization of functional brain networks, we propose a cognitive network architecture that hierarchically chunks and super-chunks switching sequences of metastable states produced by winnerless competitive heteroclinic dynamics.
What do direct care workers say would improve their jobs? Differences across settings.

PURPOSE The study's goals were to understand what changes in management practices would most improve the jobs of frontline workers from the perspective of workers themselves and to analyze differences across settings. DESIGN AND METHODS The baseline survey of direct care workers (N=3,468) conducted as part of the National Study of the Better Jobs Better Care demonstration asked the following: "What is the single most important thing your employer could do to improve your job as a direct care worker? " We coded the open-ended responses and grouped them into categories. We then compared the percentages of workers recommending changes in these categories across settings and interpreted them in the context of previous conceptual frameworks. RESULTS Across settings, workers called for more pay and better work relationships including communication; supervision; and being appreciated, listened to, and treated with respect. The fraction of workers calling for these changes and additional specific changes differed substantially across nursing facilities, assisted living facilities, and home care agencies. IMPLICATIONS To increase retention of frontline workers, policy makers should design public policies and management practices to increase pay and to improve work relationships. However, specific strategies should differ across settings.
Physical Characterization of Objects in the Geo Region with the Loiano 1.5 M Telescope

A pilot program for the physical characterization of the space debris population in high Earth orbits was started at the 152cm G.D. Cassini Telescope in Loiano, operated by the INAF Astronomical Observatory of Bologna, Italy. Several BVRI photometric images of active satellites, disposed spacecraft and upper stages were acquired during 4 nights in the year 2011 along with a number of photometric calibration fields and Solar analogue stars (spectral standards) for calibration purposes. A few High Area to Mass Ratio, HAMR, objects were observed and lightcurves were obtained for them. The paper presents the obtained data and the discussion on how to establish the physical nature and hence, possibly, the origin of the targets.
Regulation of desmosome assembly in epithelial cells: kinetics of synthesis, transport, and stabilization of desmoglein I, a major protein of the membrane core domain

Desmosomes are composed of two morphologically and biochemically distinct domains, a cytoplasmic plaque and membrane core. We have initiated a study of the synthesis and assembly of these domains in Madin-Darby canine kidney (MDCK) epithelial cells to understand the mechanisms involved in the formation of desmosomes. Previously, we reported the kinetics of assembly of two components of the cytoplasmic plaque domain, Desmoplakin I/II (Pasdar, M., and W. J. Nelson. 1988. J. Cell Biol. 106:677-685 and 106:687-699. We have now extended this analysis to include a major glycoprotein component of the membrane core domain, Desmoglein I (DGI; Mr = 150,000). Using metabolic labeling and inhibitors of glycoprotein processing and intracellular transport, we show that DGI biosynthesis is a sequential process with defined stages. In the absence of cell-cell contact, DGI enters a Triton X-100 soluble pool and is core glycosylated. The soluble DGI is then transported to the Golgi complex where it is first complex glycosylated and then titrated into an insoluble pool. The insoluble pool of DGI is subsequently transported to the plasma membrane and is degraded rapidly (t1/2 less than 4 h). Although this biosynthetic pathway occurs independently of cell-cell contact, induction of cell-cell contact results in dramatic increases in the efficiency and rate of titration of DGI from the soluble to the insoluble pool, and its transport to the plasma membrane where DGI becomes metabolically stable (t1/2 greater than 24 h). Taken together with our previous study of DPI/II, we conclude that newly synthesized components of the cytoplasmic plaque and membrane core domains are processed and assembled with different kinetics indicating that, at least initially, each domain is assembled separately in the cell. However, upon induction of cell-cell contact there is a rapid titration of both components into an insoluble and metabolically stable pool at the plasma membrane that is concurrent with desmosome assembly.
A Burkean Inquiry into Leader–Follower Identification Motives

The primary goal of this paper is to develop a rhetorically based understanding of the dynamics of the identification process between transformational or charismatic leaders and their followers. We bring to bear Burke’s theory of identification in an effort to provide a finely nuanced and deeply rooted conceptualization of follower identification that we perceive to be a weakness of the transformational/charismatic leadership discourse. A secondary goal is to evaluate leader–follower identification motives to reveal the potential for ‘questionable’ motives on the part of both leaders and followers. A dramaturgical model is utilized to reveal the dramatic struggle that underlies the leader–follower identification process. We suggest that Goffman’s views on morality and manipulation can provide a useful supplement to Burke’s theory of identification as it highlights the performative aspects of transformational and charismatic leadership.
Semantic process mining of enterprise transaction data

As large companies are building up their enterprise architecture solutions, they need torelate business process descriptions to lengthy and formally structured documents ofcorporate policies and standards. However, these documents are usually not specific toparticular tasks or processes and the user is left to read through a substantial amount ofirrelevant text to find the few fragments that are relevant. In this paper, we describe atext mining approach to establishing links between business process model elementsand relevant parts of governing documents in Statoil, one of Norway's largestcompanies. The approach builds on standard IR techniques, gives us a ranked list of textfragments for each business process activity and can easily be integrated with Statoil'senterprise architecture solution. With these ranked lists at hand, users can easily find themost relevant sections to read before carrying out their activities.
Control of a nonholonomic mobile robot using neural networks

A control structure that makes possible the integration of a kinematic controller and a neural network (NN) computed-torque controller for nonholonomic mobile robots is presented. A combined kinematic/torque control law is developed using backstepping and stability is guaranteed by Lyapunov theory. This control algorithm can be applied to the three basic nonholonomic navigation problems: tracking a reference trajectory, path following and stabilization about a desired posture. Moreover, the NN controller proposed in this work can deal with unmodelled bounded disturbances and/or unstructured unmodelled dynamics in the vehicle.
From application requests to virtual IOPs: provisioned key-value storage with Libra

Achieving predictable performance in shared cloud storage services is hard. Tenants want reservations in terms of system-wide application-level throughput, but the provider must ultimately deal with low-level IO resources at each storage node where contention arises. Such a guarantee has thus proven elusive, due to the complexities inherent to modern storage stacks: non-uniform IO amplification, unpredictable IO interference, and non-linear IO performance. This paper presents Libra, a local IO scheduling framework designed for a shared SSD-backed key-value storage system. Libra guarantees per-tenant application-request throughput while achieving high utilization. To accomplish this, Libra leverages two techniques. First, Libra tracks the IO resource consumption of a tenant's application-level requests across complex storage stack interactions, down to low-level IO operations. This allows Libra to allocate per-tenant IO resources for achieving app-request reservations based on their dynamic IO usage profile. Second, Libra uses a disk-IO cost model based on virtual IO operations (VOP) that captures the non-linear relationship between SSD IO bandwidth and IO operation (IOP) throughput. Using VOPs, Libra can both account for the true cost of an IOP and determine the amount of provisionable IO resources available under IO interference. An evaluation shows that Libra, when applied to a LevelDB-based prototype with SSD-backed storage, satisfies tenant app-request reservations and achieves accurate low-level VOP allocations over a range of workloads, while still supporting high utilization.
PERFORMANCE ANALYSIS OF THE TECHNIQUES EMPLOYED ON VARIOUS DATASETS IN IDENTIFYING THE HUMAN FACIAL EMOTION

The technique of recognizing emotion using facial expressions is a central element in human interactions. Human emotion can be easily detected with the help of facial expressions. Understanding human emotion accurately is one of the challenging tasks in the present world. Automatic emotion recognition through facial expression provides lots of flexibility in many research areas like medicine, psychology as well as in computer science.By developing systems that can detect and understand emotions, we can enhance the Human Computer Interaction. There arevarious types of feature extraction techniques as well as standard datasets have been developed for recognising emotion through facial expression. Through this paper our main motive is to review the performances ofall featureextraction techniques as well as the datasets which have been used for various types of automatic emotion recognition research works.
PRISM-II compiler and architecture

This paper discusses the architecture and compiler for a general-purpose metamorphic computing platform called PRISM-II. PRISM-II improves the performance of many computationally-intensive tasks by augmenting the functionality of the core processor with new instructions that match the characteristics of targeted applications. In essence, PRISM (processor reconfiguration through instruction set metamorphosis) is a general purpose hardware platform that behaves like an application-specific platform. Two methods for hardware synthesis, one using VHDL Designer and the other using X-BLOX, are presented and synthesis results are compared. <<ETX>>
OUTER SPACE, SELFISHNESS, AND INNOVATIVE SERVICES IN NETWORKS OF MOBILE INDIVIDUALS

I certify that I have read this dissertation and that, in my opinion, it is fully adequate in scope and quality as a dissertation for the degree of Doctor of Philosophy. Dedikuar mamit dhe babit. Acknowledgements First and foremost I would like to thank my advisor, Prof. Alessandro Mei, for all his support during these years. He shared with me lots of excellent, elegant and inspiring ideas, and reinvented my way of fact-finding. He taught me everything from how to deal with difficulties, how to start thinking about new cool problems, how to approach them step by step, to how to achieve the highest goals. He always hold me to the highest standards and pushed me to do my best work all the time, yet reminding me every single moment, even in the toughest ones, of how fun research is! I'd really wish to become as skillful, enthusiastic , energetic, judicious, perspicacious, and outstandingly keen about both scientific research and teaching as Prof. Mei is, and, someday, to be able to command an audience and supervise students as awesomely as he can. I want to express special gratitude to my High School Maths teacher Prof. Raimond Gumeni, for always believing in me. I want to thank all my co-workers, phd colleagues, and all the people at the CS Department for all the wonderful moments passed during these three years. A remarkable thank-you goes to the members of my internal thesis committee, Prof. Roberto and Prof. Radha Poovendran, for the wonderful job they've done with my dissertation and for their excellent comments and advices on the matter. Lastly, I want to thank my wonderful parents for supporting me during all my education studies, for always believing in me, and for teaching me that the best way of being ambitious is to be so with yourself. I'm blessed to have such awesome parents, and I'm really proud of them.
Effects of Bergamot (Citrus bergamia (Risso) Wright & Arn.) Essential Oil Aromatherapy on Mood States, Parasympathetic Nervous System Activity, and Salivary Cortisol Levels in 41 Healthy Females

Background: Bergamot essential oil (BEO) is commonly used against psychological stress and anxiety in aromatherapy. The primary aim of the present study was to obtain first clinical evidence for these psychological and physiological effects. A secondary aim was to achieve some fundamental understanding of the relevant pharmacological processes. Methods: Endocrinological, physiological, and psychological effects of BEO vapor inhalation on 41 healthy females were tested using a random crossover study design. Volunteers were exposed to 3 experimental setups (rest (R), rest + water vapor (RW), rest + water vapor + bergamot essential oil (RWB)) for 15 min each. Immediately after each setup, saliva samples were collected and the volunteers rested for 10 min. Subsequently, they completed the Profile of Mood States, State-Trait Anxiety Inventory, and Fatigue Self-Check List. High-frequency (HF) heart rate values, an indicator for parasympathetic nervous system activity, were calculated from heart rate variability values measured both during the 15 min of the experiment and during the subsequent 10 min of rest. Salivary cortisol (CS) levels in the saliva samples were analyzed using ELISA. Results: CS of all 3 conditions R, RW, and RWB were found to be significantly distinct (p = 0.003). In the subsequent multiple comparison test, the CS value of RWB was significantly lower when compared to the R setup. When comparing the HF values of the RWB setup during the 10 min of rest after the experiment to those of RW, this parameter was significantly increased (p = 0.026) in the RWB setup for which scores for negative emotions and fatigue were also improved. Conclusion: These results demonstrate that BEO inhaled together with water vapor exerts psychological and physiological effects in a relatively short time.
Distributed Machine Learning via Sufficient Factor Broadcasting

Matrix-parametrized models, including multiclass logistic regression and sparse coding, are used in machine learning (ML) applications ranging from computer vision to computational biology. When these models are applied to large-scale ML problems starting at millions of samples and tens of thousands of classes, their parameter matrix can grow at an unexpected rate, resulting in high parameter synchronization costs that greatly slow down distributed learning. To address this issue, we propose a Sufficient Factor Broadcasting (SFB) computation model for efficient distributed learning of a large family of matrix-parameterized models, which share the following property: the parameter update computed on each data sample is a rank-1 matrix, i.e., the outer product of two "sufficient factors" (SFs). By broadcasting the SFs among worker machines and reconstructing the update matrices locally at each worker, SFB improves communication efficiency --- communication costs are linear in the parameter matrix's dimensions, rather than quadratic --- without affecting computational correctness. We present a theoretical convergence analysis of SFB, and empirically corroborate its efficiency on four different matrix-parametrized ML models.
Human-Animal Relationship: Understanding Animal Rights in the Islamic Ecological Paradigm

Animals have encountered cruelty and suffering throughout the ages. It is something perpetrated up till this day, particularly, in factory farms, animal laboratories, and even in the name of sports or amusement. However, since the second half of the twentieth century, there has been growing concerns for animal welfare and the protection of animal rights within the discourse of environmentalism, developed mainly in the West. Nevertheless, a recently developed Islamic Ecological Paradigm (IEP) rooted in the classical Islamic traditions contests the "Western" monopoly of modern environmentalism, suggesting that there is much in Islamic traditions dealing with environmental issues including non-human animal species. IEP asserts that several centuries ago Islamic traditions significantly focused on and strongly advocated for animal welfare and animal rights. This paper explores and examines animal rights within the broader spectrum of Islamic environmentalism or Islamic eco-ethic. While the philosophical roots of IEP concerning animal rights date far back in seventh century, it can potentially make both ethical and educational contributions to the twenty-first century environmentalism and animal rights movements.