Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient attacks on robust ring oscillator PUF with enhanced challenge-response set

Physically Unclonable Function (PUF) circuits are an important class of hardware security primitives that promise a paradigm shift in applied cryptography. Ring Oscillator PUF (ROPUF) is an important PUF variant, but it suffers from hardware overhead limitations, which in turn restricts the size of its challenge space. To overcome this fundamental shortcoming, improved ROPUF variants based on the subset selection concept have been proposed, which significantly “expand” the challenge space of a ROPUF at acceptable hardware overhead. In this paper, we develop cryptanalytic attacks on a previously proposed low-overhead and robust ROPUF variant. The proposed attacks are practical as they have quadratic time and data complexities in the worst case. We demonstrate the effectiveness of the proposed attack by successfully attacking a public domain dataset acquired from FPGA implementations.
Botnets – The Silent Threat

opinion on topics ENISA considers important emerging risks or key security components. This paper has been written and reviewed by the group of experts listed below who work in the area of malware analysis. The paper aims to provide a useful introduction to the rising problem of botnets. It describes the reasons for concern, the infection vectors of bots, the motivation of their creators and expected trends. It concludes with recommendations to policy-makers, providers and end-users on how to counter this serious threat. Audience The management summary is aimed at high-level decision-makers seeking a basic understanding of the problem. The remainder of the paper explains the situation in more detail for those who are responsible for IT in public or private organisations.
Hemoglobin A1c Point-of-Care Assays; A New World with a Lot of Consequences!

Background: Point-of-care instruments for the measurement of hemoglobin A1c (HbA1c) may improve the glycemic control of people with diabetes by providing a rapid result if the performance of the instruments used is acceptable. A 0.5% HbA1c difference between successive results is considered a clinically relevant change. With this in mind, the In2it from Bio-Rad and the DCA Vantage from Siemens were evaluated according to Clinical and Laboratory Standards Institute (CLSI) protocols. Methods: The CLSI protocols EP-5 and EP-9 were applied to investigate precision, accuracy, and bias. The bias was compared with three certified secondary reference measurement procedures. Differences between capillary and venous blood were investigated by an end-user group consisting of nurse practitioners at a diabetes care center. Results: At HbA1c levels of 5.1 and 11.2%, total coefficients of variation (CV) for the In2it were 4.9 and 3.3%, respectively, and for the DCA Vantage were 1.7 to 1.8% and 3.7 to 5.5% depending on the lot number of the cartridges. Method comparisons showed significant lot number-dependent results for the In2it and the DCA Vantage compared with the three reference methods. No overall difference was observed between capillary and venous blood for both methods. Conclusion: Performance results of the In2it and the DCA Vantage showed variable and lot number-dependent results. To maintain the interlaboratory CV of 5% for HbA1c, the Clinical Laboratory Improvement Amendments rules for waived point-of-care instruments should be revised. An obligation for participating in external quality schemes and taking adequate action should be considered for POC instruments that perform poorly.
ClassAMP: A Prediction Tool for Classification of Antimicrobial Peptides

Antimicrobial peptides (AMPs) are gaining popularity as anti-infective agents. Information on sequence features that contribute to target specificity of AMPs will aid in accelerating drug discovery programs involving them. In this study, an algorithm called ClassAMP using Random Forests (RFs) and Support Vector Machines (SVMs) has been developed to predict the propensity of a protein sequence to have antibacterial, antifungal, or antiviral activity. ClassAMP is available at http://www.bicnirrh. res.in/classamp/.
Can Lexicon Bad Smells Improve Fault Prediction?

In software development, early identification of fault-prone classes can save a considerable amount of resources. In the literature, source code structural metrics have been widely investigated as one of the factors that can be used to identify faulty classes. Structural metrics measure code complexity, one aspect of the source code quality. Complexity might affect program understanding and hence increase the likelihood of inserting errors in a class. Besides the structural metrics, we believe that the quality of the identifiers used in the code may also affect program understanding and thus increase the likelihood of error insertion. In this study, we measure the quality of identifiers using the number of Lexicon Bad Smells (LBS) they contain. We investigate whether using LBS in addition to structural metrics improves fault prediction. To conduct the investigation, we assess the prediction capability of a model while using i) only structural metrics, and ii) structural metrics and LBS. The results on three open source systems, ArgoUML, Rhino, and Eclipse, indicate that there is an improvement in the majority of the cases.
Accuracy and Duty-Cycle of FTSP on a LPL-MAC

Synchronization accuracy and energy efficiency are two of the most important requirements of a synchronization protocol for wireless sensor networks (WSNs). Typically, synchronization protocols for WSNs like FTSP rely on periodic message exchange in order to achieve a sufficient level of accuracy. A higher accuracy therefore comes at the expense of an increased energy consumption. In this paper, we introduce an analytic framework aimed at analyzing how accuracy and energy consumption are affected by the synchronization period and the radio duty cycle, using the example of FTSP running on top of a low-power listening (LPL) MAC protocol. The model exposes the hidden dependencies between protocol parameters and application requirements, which allows for using standard tools to generate feasible as well as optimal protocol configurations.
Towards Autonomic DDoS Mitigation using Software Defined Networking

Distributed Denial of Service attacks (DDoS) have remained as one of the most destructive attacks in the Internet for over two decades. Despite tremendous efforts on the design of DDoS defense strategies, few of them have been considered for widespread deployment due to strong design assumptions on the Internet infrastructure, prohibitive operational costs and complexity. Recently, the emergence of Software Defined Networking (SDN) has offered a solution to reduce network management complexity. It is also believed to facilitate security management thanks to its programmability. To explore the advantages of using SDN to mitigate DDoS attacks, we propose a distributed collaborative framework that allows the customers to request DDoS mitigation service from ISPs. Upon request, ISPs can change the label of the anomalous traffic and redirect them to security middleboxes, while attack detection and analysis modules are deployed at customer side, avoiding privacy leakage and other legal concerns. Our preliminary analysis demonstrates that SDN has promising potential to enable autonomic mitigation of DDoS attacks, as well as other large-scale attacks
Decreased mitochondrial carnitine translocase in skeletal muscles impairs utilization of fatty acids in insulin-resistant patients.

Insulin resistance (IR) and its health consequences (diabetes, hypertension, cardiovascular disease, obesity etc.) affect between 25 and 35% of Westernized populations. Decreased fatty acid (FA) oxidation in skeletal muscle is implicated in obesity-related IR. Carnitine-acylcarnitine translocase (CACT) transports long-chain FAs both into mitochondria (as carnitine esters for energy-generating processes) and out of mitochondria. To determine whether CACT activity correlates with decreased FA oxidation we measured CACT concentrations in cellular and mitochondrial extracts from the skeletal muscle of 19 obese IR individuals and of 19 lean controls. We also evaluated carnitine transport in skeletal muscle mitochondria in both groups. Mitochondrial CACT was decreased at translational and transductional level, and carnitine-carnitine and acylcarnitine-carnitine exchange rates were significantly lower in IR subjects. Aberrant acylcarnitine flux into mitochondria was not correlated with decreased activity of other components of the mitochondrial carnitine system (i.e., carnitine palmitoyl transferase-I and II). Our data suggest that by restraining entry of FA-coenzyme A into mitochondria, low CACT levels increase cytosolic FA levels and their incorporation into glycerolipids. The low level of CACT in IR muscle may contribute to the elevated muscle concentrations of triglycerides, diacylglycerol, and FA-coenzyme A characteristic of IR muscle.
Tilting Plant Metabolism for Improved Metabolite Biosynthesis and Enhanced Human Benefit

The immense chemical diversity of plant-derived secondary metabolites coupled with their vast array of biological functions has seen this group of compounds attract considerable research interest across a range of research disciplines. Medicinal and aromatic plants, in particular, have been exploited for this biogenic pool of phytochemicals for products such as pharmaceuticals, fragrances, dyes, and insecticides, among others. With consumers showing increasing interests in these products, innovative biotechnological techniques are being developed and employed to alter plant secondary metabolism in efforts to improve on the quality and quantity of specific metabolites of interest. This review provides an overview of the biosynthesis for phytochemical compounds with medicinal and other related properties and their associated biological activities. It also provides an insight into how their biosynthesis/biosynthetic pathways have been modified/altered to enhance production.
The Life Cycle of Us Economic Expansions

Graphs that allow side by side comparisons of the six longer US expansions since 1950 suggest that these expansions have four distinct phases: (1) a high growth recovery during which the rate of unemployment declines to its pre-recession level, (2) a modest growth plateau during which the rate of unemployment is constant, (3) a growth spurt that drives unemployment down further and (4) a second plateau with modest growth and constant rate of unemployment. There have been only three expansions that have experienced the spurt and none has experienced a second spurt. These phases involve substantially different rates of GDP growth, but within each of these four phases GDP growth is largely unpredictable. Forecast accuracy thus comes mostly from understanding the transitions. This requires both data and economics. The economics takes the form of a predator/prey model of the cycle, where the prey are investment opportunities and the predators are entrepreneurs. A probit model of the transition into recession raises concerns about how much longer the aged Bush/Clinton expansion can last.
Mitochondria buffer physiological calcium loads in cultured rat dorsal root ganglion neurons

We sought to determine whether low-affinity, high-capacity mitochondrial Ca2+ uptake contributes to buffering physiological Ca2+ loads in sensory neurons. Intracellular free calcium concentration ([Ca2+]i) and intracellular free hydrogen ion concentration ([H+]i) were measured in single rat dorsal root ganglion (DRG) neurons grown in primary culture using indo-1 and carboxy-SNARF-based dual emission microfluorimetry. Field potential stimulation evoked action potential- mediated increases in [Ca2+]. Brief trains of action potentials elicited [Ca2+]i transients that recovered to basal levels by a single exponential process. Trains of > 25 action potentials elicited larger increases in [Ca2+]i, recovery from which consisted of three distinct phases. During a rapid initial phase [Ca2+]i decreased to a plateau level (450–550 nM). The plateau was followed by a slow return to basal [Ca2+]i [Ca2+]i transients elicited by 40–50 action potentials in the presence of the mitochondrial uncoupler carbonyl cyanide chlorophenyl hydrazone (CCCP), or the electron transport inhibitor antimycin A1, lacked the plateau, and the recovery to basal [Ca2+]i consisted of a single slow phase. Depolarization with 50 mM K+ produced a multiphasic [Ca2+]i transient and increased [H+]i from 74 +/- 3 to 107 +/- 8 nM. The rise in [H+]i was dependent upon extracellular Ca2+ and was inhibited by mitochondrial poisons. With mitochondrial Ca2+ buffering pharmacologically blocked, the recovery to basal [Ca2+]i was unaffected by removal of extracellular Na+. We conclude that large Ca2+ loads are initially buffered by fast mitochondrial sequestration that effectively uncouples electron transport from ATP synthesis, leading to an increase in [H+]i. Small Ca2+ loads are buffered by a nonmitochondrial, Na(+)- independent process.
The Rutgers Arm: An Upper-Extremity Rehabilitation System in Virtual Reality

Stroke is one of the leading causes of death and disability worldwide. Its prevalence calls for innovative rehabilitation methods for post-stroke patients. The Rutgers Arm is a novel arm rehabilitation system consisting of a special table, 3D tracker, custom forearm support, PC workstation, library of Java 3D VR exercises, clinical database module, and a tele-rehabilitation extension. The Rutgers Arm was tested on a chronic stroke subject, under local and tele-rehabilitation conditions, over five weeks of training. Case study results show improvements in arm motor control, shoulder range of motion, and (as illustrated by improvements in computerized measures and in Fugl-Meyer test scores). The tele-rehabilitation portion of training showed that exercise duration, level of difficulty and patient motivation, were maintained. A one-week-retention trial showed that most of the gains were maintained (or improved on) by the subject.
Yield Curve

This paper provides a brief survey of the relationship between the yield curve and future changes in interest rates and inflation. The expectations hypothesis of the term structure indicates . that when the yield curve is upward sloping, future short-term and long-term interest rates are expected to rise. Empirical evidence finds that as predicted by the expectations hypothesis, yield spreads are positively correlated with future changes in short-term interest rates, particularly at long horizons. However, yield spreads are negatively correlated with next period's change in long-term interest rates, the opposite prediction of the expectations hypothesis. Empirical evidence also suggests that the yield curve has almost no ability to forecast future inflation changes for short horizons: however, at horizons of a year or greater, the yield curve contains a great deal of information about the future path of inflation.
Behind the Scenes: Sources of Complementarity in R&D

Even though management consultants increasingly recommend that in-house research be outsourced, little is known about the conditions favoring substitution or complementarity between internal R&D and external technology acquisition. In this paper, we attempt to provide a deeper understanding of the firm-level drivers of complementarity between these two types of investments through the structural estimation of a flexible innovation production function, such as the translog. Our empirical analysis is based on a unique panel dataset on the R&D and in-licensing expenditures of 94 global pharmaceutical firms active in drug development between 1997 and 2005. Our results suggest that internal R&D and in-licensing in the pharmaceutical industry were neither complements nor substitutes during the study period. However, we find that the degree of complementarity is enhanced for firms with stronger absorptive capacity, economies of scope, and past licensing experience.
Co-operative governance : pathways to poverty reduction? : the case of Kenya

A reviving and growing co-operative movement across the globe is attracting greater attention, leading to recognition of the important role that it can play in reducing poverty from actors such as national governments and development partners. However, the history of co-operative development in many developing countries has shown us the risks of such attention on the co-operative model, where external stakeholders direct the objectives and activities of co-operatives. This research extends understanding of cooperative governance, and discusses how it can be used to safeguard the co-operative form. It does this to show how member control and decision-making can remain central within a revived co-operative movement and contribute to reducing poverty. I develop a conceptual framework through ‘pathways’ that extend existing co-operative governance concepts and theories to the African context. The pathways show how a balance in different governance areas can combine to influence the way a co-operative operates, and the impact that this can have on poverty at the village and household levels. I operationalise the pathways through two case study co-operatives in rural Kenya, with contrasting governance characteristics. Using a qualitative research approach with participatory methods, I compare the balance in the two co-operatives’ different governance areas, tracing their direct and indirect links to poverty outcomes in two case study villages (where each of the co-operatives have a large number of members), as well as in member and non-member households. The research shows that a balance in the relationships between internal and external stakeholders, as well as strong member participation and loyalty to the co-operative, can combine to allow a balance in the economic and social outcomes of co-operatives - essential to reducing poverty in communities and households. Striving towards this balance in co-operative governance is crucial to maximising impact on poverty.
Proof Systems for Inductive Reasoning in the Logic of Bunched Implications

We report on our early progress in developing suitable frameworks for inductive reasoning in separation logic and related logics for low-level program verification, following the approach of our previous work on sequent proof systems for first-order logic with inductive definitions. We extend a first-order predicate version of the logic of bunched implications, BI — of which separation logic is a special instance — with a framework for inductively defined predicates in which both the additive and multiplicative conjunctions of BI may occur in the premises of definitions. We then formulate two Gentzen-type proof systems for this logic: a traditional finitary system incorporating explicit induction rules; and a system for cyclic proof in which the induction rules are replaced by weaker case-split rules, and proofs are derivation trees with “back edges”, satisfying a global syntactic condition ensuring soundness. We illustrate our framework and proof systems with simple examples that indicate that, in our setting, cyclic proof may enjoy certain advantages over the traditional induction approach.
The Study of E-Commerce System Integration Based on PDM

With the development of E-commerce and the coming of information age, Chinese manufacturing industry has been faced with vast opportunities and challenges. How to realize comprehensive information is enterprises' pursuit. The primary task is to establish reasonable and efficient management information system. Through the analysis of the principle and architecture of PDM and the roles of E- commerce in the development, the paper offers E-commerce system structure and work flow based on PDM, which is helpful to resolve the corresponding problems appearing in E-commerce system integration. Index Terms—E-commerce, PDM, integration
Understanding Knowledge Sharing In Organizations: Further Questions Of Research Through A Social Cognitive Perspective

Enabling knowledge sharing among individuals in organizations is fundamental to innovation and organizational success. Nevertheless, despite receiving great attention among both academics and practitioners, knowledge sharing research is still searching for integrated framework. Recent literature reviews shows that most of the existing research has centered on a macro perspective, attaching less emphasis on the integration of the individual in the process. Being aware of this, an increasing group of scholars have proposed a multi-level integration of the individual and the organizational perspectives. This paper argues that this new approach that is grounded on sociology provides appropriate research questions, but might not be enough to successfully answer them, since is rooted in a sociological vision of the individual. Knowledge sharing literature might pay more attention to the reciprocal interaction of personal factors, individual behavior and organizational environment. A possible way to fill this gap can be by viewing the topic through the lens of the social cognitive theory. This theory permits a better integration of existing research of some psychosocial topics such as vicarious learning, self-efficacy, cognitive biases and schemas.
Controlled hidden Markov models for dynamically adapting patch clamp experiment to estimate Nernst potential of single-ion channels

This paper presents novel kernel-based stochastic learning algorithms for controlling the kinetics of single-ion channels in a patch clamp experiment. The algorithms yield efficient estimates of the equilibrium (Nernst) potential of an ion channel. The equilibrium potential of an ion channel is the applied external potential difference required to maintain electrochemical equilibrium across the ion channel. The algorithm adaptively controls the exploration of the learning algorithm to achieve an optimal balance between exploration and exploitation. An important feature of the resulting algorithm is that it is guaranteed to minimize the experimental effort. We illustrate the efficiency of the algorithms for the experimentally determined current voltage curve of a bi-ionic single potassium ion channel.
Personalized Cancer Risk Assessments for Space Radiation Exposures

Individuals differ in their susceptibility to radiogenic cancers, and there is evidence that this inter-individual susceptibility extends to HZE ion-induced carcinogenesis. Three components of individual risk: sex, age at exposure, and prior tobacco use, are already incorporated into the NASA cancer risk model used to determine safe days in space for US astronauts. Here, we examine other risk factors that could potentially be included in risk calculations. These include personal and family medical history, the presence of pre-malignant cells that could undergo malignant transformation as a consequence of radiation exposure, the results from phenotypic assays of radiosensitivity, heritable genetic polymorphisms associated with radiosensitivity, and postflight monitoring. Inclusion of these additional risk or risk reduction factors has the potential to personalize risk estimates for individual astronauts and could influence the determination of safe days in space. We consider how this type of assessment could be used and explore how the provisions of the federal Genetic Information Non-discrimination Act could impact the collection, dissemination and use of this information by NASA.