Miracle-dz/UniFAR-FTUs huggingface dataset:
Remote estimation of carbon dioxide uptake by a Mediterranean forest

The estimation of the carbon balance in ecosystems, regions, and the biosphere is currently one of the main concerns in the study of the ecology of global change. Current remote sensing methodologies for estimating gross primary productivity are not satisfactory because they rely too heavily on (i) the availability of climatic data, (ii) the definition of land‐use cover, and (iii) the assumptions of the effects of these two factors on the radiation‐use efficiency of vegetation (RUE). A new methodology is urgently needed that will actually assess RUE and overcome the problems associated with the capture of fluctuations in carbon absorption in space and over time. Remote sensing techniques such as the widely used reflectance vegetation indices (e.g. NDVI, EVI) allow green plant biomass and therefore plant photosynthetic capacity to be assessed. However, there are vegetation types, such as the Mediterranean forests, with a very low seasonality of these vegetation indices and a high seasonality of carbon uptake. In these cases it is important to detect how much of this capacity is actually realized, which is a much more challenging goal. The photochemical reflectance index (PRI) derived from freely available satellite information (MODIS sensor) presented for a 5‐year analysis for a Mediterranean forest a positive relationship with the RUE. Thus, we show that it is possible to estimate RUE and GPP in real time and therefore actual carbon uptake of Mediterranean forests at ecosystem level using the PRI. This conceptual and technological advancement would avoid the need to rely on the sometimes unreliable maximum RUE.
Bell's palsy: Surgery based upon prognostic indicators and results

We studied 164 patients with Bell's palsy prospectively over the six‐year period between August 1974 and June 1980. We found that the results of measuring tear production, sub‐mandibular salivary flow, the response to maximal stimulation, and evoked electromyography gave us sufficient information to group these patients according to prognosis —either unfavorable or favorable — for spontaneous return of facial function. When the test results were 26% or more of normal, 90% of the patients had complete recovery of function; these patients were given a favorable prognosis on the basis of the results of tests described above.
A Systematic Design of Tamper-Resistant Galois-Field Arithmetic Circuits Based on Threshold Implementation with (d + 1) Input Shares

This paper presents a systematic design of tamperresistantGalois-Field (GF) arithmetic circuits based on ThresholdImplementation (TI) where a secret variable is represented withmultiple variables, called shares, given by random numbers. TI isone of the countermeasures against Differential Power Analysis(DPA) on cryptographic hardware. The security order of TIdepends on the number of shares. The minimum number ofshares to be resistant dth-order DPA is said to be (d+1). Whilethe construction of GF arithmetic circuits of quadratic functionbased on TI with (d + 1) shares is known, it is not known howto construct other types of circuits based on it. In this paper, wepresent a generalization and systematic method of constructingthe TI with (d + 1) input shares for any kind of GF arithmeticcircuit in order to design a larger variety of tamper-resistantGF arithmetic circuits. We then apply the proposed method toa cryptographic hardware design in order to demonstrate its efficiency.
Translational Circuits [A Circuit for All Seasons]

Translational circuits are periodically driven, time-variant systems and encompass topologies such as "commutated networks" and "N-path filters". These systems cause frequency "translation" (shift) of impedances and transfer functions, a useful property that has led to myriad new and interesting concepts in RF design. In this article, we study the operation principles of these circuits.
Phasic excitation of ventral tegmental dopamine neurons potentiates the initiation of conditioned approach behavior: parametric and reinforcement-schedule analyses

Midbrain dopamine neurons are implicated in motivation and learning. However, it is unclear how phasic excitation of dopamine neurons, which is implicated in learning, is involved in motivation. Here we used a self-stimulation procedure to examine how mice seek for optogenetically-induced phasic excitation of dopamine neurons, with an emphasis on the temporal dimension. TH-Cre transgenic mice received adeno-associated viral vectors encoding channelrhodopsin-2 into the ventral tegmental area, resulting in selective expression of the opsin in dopamine neurons. These mice were trained to press on a lever for photo-pulse trains that phasically excited dopamine neurons. They learned to self-stimulate in a fast, constant manner, and rapidly reduced pressing during extinction. We first determined effective parameters of photo-pulse trains in self-stimulation. Lever-press rates changed as a function of the manipulation of pulse number, duration, intensity, and frequency. We then examined effects of interval and ratio schedules of reinforcement on photo-pulse train reinforcement, which was contrasted with food reinforcement. Reinforcement with food inhibited lever pressing for a few seconds, after which pressing was robustly regulated in a goal-directed manner. In contrast, phasic excitation of dopamine neurons robustly potentiated the initiation of lever pressing; however, this effect did not last more than 1 s and quickly diminished. Indeed, response rates markedly decreased when lever pressing was reinforced with inter-reinforcement interval schedules of 3 or 10 s or ratio schedules requiring multiple responses per reinforcement. Thus, phasic excitation of dopamine neurons briefly potentiates the initiation of approach behavior with apparent lack of long-term motivational regulation.
Lattice-Based Threshold Changeability for Standard Shamir Secret-Sharing Schemes

We consider the problem of increasing the threshold parameter of a secret-sharing scheme after the setup (share distribution) phase, without further communication between the dealer and the shareholders. Previous solutions to this problem require one to start off with a nonstandard scheme designed specifically for this purpose, or to have communication between shareholders. In contrast, we show how to increase the threshold parameter of the standard Shamir secret-sharing scheme without communication between the shareholders. Our technique can thus be applied to existing Shamir schemes even if they were set up without consideration to future threshold increases. Our method is a new positive cryptographic application for lattice reduction algorithms, inspired by recent work on lattice-based list decoding of Reed-Solomon codes with noise bounded in the Lee norm. We use fundamental results from the theory of lattices (geometry of numbers) to prove quantitative statements about the information-theoretic security of our construction. These lattice-based security proof techniques may be of independent interest.
How does lead induce male infertility?

An important part of male infertility of unknown etiology may be attributed to various environmental and occupational exposures to toxic substances, such as lead. The reproductive effects of lead are complex and appear to involve multiple pathways, not all of which are fully understood. It is still unclear, for example, if male reproductive issues in lead-exposed persons are mostly related to the disruption of reproductive hormones, whether the problems are due to the lead’s direct effects on the gonads, or both? This question has been difficult to answer, because lead, especially at high levels, may adversely affect many human organs. Although lead can potentially reduce male fertility by decreasing sperm count and motility, inducing abnormal morphology and affecting functional parameters; not all studies have been able to clearly demonstrate such findings. In addition, research has shown that the blood-testis barrier can protect testicular cells from direct exposure to high levels of blood lead. For these reasons and considering the wide spectrum of lead toxicity on reproductive hormones, the present review suggests that lead’s main influence on male reproduction probably occurs by altering the reproductive hormonal axis and the hormonal control on spermatogenesis, rather than by a direct toxic effect on the seminiferous tubules of the testes. As blood lead concentrations below the currently accepted worker protection standard may still adversely affect male fertility, future studies should aim to establish more concrete links between lead exposure (especially at low levels) and subsequent male infertility. Research should also pay more attention to lead’s effects on reducing male fertility rates based on not only hormonal axis alteration, but also on the changes in sperm characteristic among exposed subjects.
Effect of Fly Ash Fortification in the Manufacture Process of Making Concrete towards Characteristics of Concrete in Sulfuric Acid Solution

Fly ash is a silica or alumino silica material that c n be used as a constituent of cement in the conc rete manufacturing process. Utilization of fly ash aims to improve dur ability and minimize the reduction of concrete’s co mpressive strength exposed to an acidic environment, which can be achi eved through the pozzolanic reaction of fly ash wit h Ca(OH)2 within concrete. The reduced content of Ca(OH) 2 through pozzolanic reaction will minimize the tendcy of ettringite formation (compounds that cause deterioration and d ecrease the compressive strength of concrete). In o rder to determine the relation between fly ash replenishmen t into concrete with concrete’s characteristics (co mpressive strength and durability) under acidic environment, the resea rch is conducted by varying the fly ash composition ra ging from 0%, 5%, 25%, 50%, up to 75%, and the concentration of H2SO4 solution as an immersion medium ranging from 0%, 5%, 10%, up to 15% (v/v). The research is carried o ut by immersing the concrete samples for 4 days in H2SO4 solution with various concentrations. Characterization of co ncrete’s durability and compressive strength is rev iewed from the concrete’s weight loss percentage and reduction of concrete’s compressive strength percentage after im mersion. Based on the research results, for each variation of H 2SO4 concentration used, the minimum concrete’s weight loss percentage (maximum durability) and the minimum reduction of c n rete’s compressive strength percentage is found in the use of fly ash by 75%. For each concentration variations o f H2SO4 solution as an immersion medium ranging from 5%, 1 0%, up to 15% (v/v), the minimum concrete’s weight loss percentage was 0.47%, 0.87%, 1.28% (respectively), whilst the minimum reduction of concrete’s compressive strengt h percentage was 5.71%, 14.29%, 17.14% (respectivel y). It was concluded that the use of fly ash can improve the d urability and minimize the reduction of compressive strength of concrete exposed to an acidic environment.
Markov switching models for time series data with dramatic jumps

In this research, the Markov switching autoregressive (MS-AR) model and six different time series modeling approaches are considered. These models are compared according to their performance for capturing the Iranian exchange rate series. The series has dramatic jump in early 2002 which coincides with the change in policy of the exchange rate regime. Our criteria are based on the AIC and BIC values. The results indicate that the MS-AR model can be considered as useful model, with the best fit, to evaluate the behaviors of Iran’s exchange rate
In Colorectal Liver Metastases, the Presence of Extrahepatic Disease Correlates with the Pathology of the Primary Tumour

Background. FDG-PET scan detects extrahepatic metastases in 20% of patients with colorectal liver metastases but it is reported to have approximately 16% false negative rates. Patients and Methods. Patients who had PET scan for metastatic colorectal cancer at Westmead Hospital between March 2006 and March 2010 were reviewed retrospectively. The results of PET scan were correlated with tumour characteristics that were thought to affect the overall prognosis. Results. Degree of tumour differentiation and vascular invasion were significantly predictive for the presence of extrahepatic disease on PET scan, also did the level of CEA. Conclusion. The detection of extrahepatic disease in colorectal liver metastases correlates with the biologic behaviour of the primary tumour. Poorly differentiated tumours and those with lymphovascular invasion behave in aggressive fashion and likely to have wide-spread metastases. This should be considered when contemplating liver resection for colorectal metastases.
Structural Vulnerability Assessment of Community-Based Routing in Opportunistic Networks

Opportunistic networks enable mobile devices to communicate with each other through routes that are built dynamically, while messages are en route between the sender and the destination(s). The social structure and interaction of users of such devices dictate the performance of routing protocols in those networks. Community structures, commonly exhibited by social networks, is also observed in the encounter patterns in opportunistic networks and has an astounding impact in designing forwarding algorithms for such types of networks. In this paper, we explore the structural vulnerability of social-based forwarding and routing methods in opportunistic networks. In particular, we introduce Community Vulnerability Assessment (CVA), a new problem on assessing the performance reliability of opportunistic routing strategies in Delay Tolerant Networks (DTN) from a community structure point of view. Given a positive number k, CVA aims to find out the k most vulnerable devices in the network whose non-participation (due to out-of-service or permanent out-of-range) transforms the current network community structure to a totally different one. As the first study in this direction, we analyze and provide key insights into the separation of network communities, evaluated via the Normalized Mutual Information (NMI). Based on these findings, we suggest an approximation algorithm for the special case when k 1/4 1, and a heuristic, genEdge, for the general case. To certify the effectiveness of our proposed approaches, we first test them on synthesized data with known community structures, and then we show the impact of node removal on community structures in real social networks. Finally we evaluate the performance via different forwarding and routing strategies in multiple real-world DTN traces. Our results indicate that, in many forwarding and routing methods, the nonparticipation of only some important devices is significant enough to degrade the entire network's performance.
Transforming growth factor β1 enhances expression of 50 kDa protein related to 2′‐5′ oligoadenylate synthetase in human sperm cells

Human cellular polypeptide factors, namely interferon‐α, interferon‐γ, transforming growth factor (TGF)‐α, and TGF‐β, were analyzed for their effect on motility of human sperm cells. Both interferons caused an inhibition of sperm cell motility due to direct cytotoxic effects without inducing 2′‐5′ oligoadenylate [2–5(A)]synthetase activity. TGF‐α affected neither motility nor the levels of 2–5(A) synthetase in sperm cells. TGF‐β, had no affect on sperm motility, yet it caused an induction of 2–5(A)synthetase activity. Western immunoblot analysis of TGF‐β1‐treated sperm indicated an enhancement of a 50 kDa protein. Metabolic labeling of sperm cells revealed biosynthesis of one major protein of 50 kDa and at least five minor proteins in the range of 30–92 kDa; the level of 50 kDa protein increased after treatment with TGF‐β1. The treatment of sperm cells with TGF‐β1 did not affect their penetration in zona‐free hamster eggs (SPA). These results indicate that TGF‐β1 enhances expression of a 50 kDa protein related to 2–5(A)synthetase in human sperm cells along with other minor proteins, and this increase does not affect sperm motility and SPA.
Benchmarking GPUs with a Parallel Lattice-Boltzmann Code

Accelerators are an increasingly common option to boost performance of codes that require extensive number crunching. In this paper we report on our experience with NVIDIA accelerators to study fluid systems using the Lattice Boltzmann (LB) method. The regular structure of LB algorithms makes them suitable for processor architectures with a large degree of parallelism, such as recent multi- and many-core processors and GPUs; however, the challenge of exploiting a large fraction of the theoretically available performance of this new class of processors is not easily met. We consider a state-of-theart two-dimensional LB model based on 37 populations (a D2Q37 model), that accurately reproduces the thermo-hydrodynamics of a 2D-fluid obeying the equation-of-state of a perfect gas. The computational features of this model make it a significant benchmark to analyze the performance of new computational platforms, since critical kernels in this code require both high memory-bandwidth on sparse memory addressing patterns and floating-point throughput. In this paper we consider two recent classes of GPU boards based on the Fermi and Kepler architectures; we describe in details all steps done to implement and optimize our LB code and analyze its performance first on single- GPU systems, and then on parallel multi-GPU systems based on one node as well as on a cluster of many nodes; in the latter case we use CUDA-aware MPI as an abstraction layer to assess the advantages of advanced GPU-to-GPU communication technologies like GPUDirect. On our implementation, aggregate sustained performance of the most compute intensive part of the code breaks the 1 double-precision Tflops barrier on a single-host system with two GPUs.
Prediction of Clinical Factors Associated with Pandemic Influenza A (H1N1) 2009 in Pakistan

Background Influenza is a viral infection that can lead to serious complications and death(s) in vulnerable groups if not diagnosed and managed in a timely manner. This study was conducted to improve the accuracy of predicting influenza through various clinical and statistical models. Methodology A retrospective cross sectional analysis was done on demographic and epidemiological data collected from March 2009 to March 2010. Patients were classified as ILI or SARI using WHO case definitions. Respiratory specimens were tested by RT-PCR. Clinical symptoms and co-morbid conditions were analyzed using binary logistic regression models. Results In the first approach, analysis compared children (≤12) and adults (>12). Of 1,243 cases, 262 (21%) tested positive for A(H1N1)pdm09 and the proportion of children (≤12) and adults (>12) were 27% and 73% respectively. Four symptoms predicted influenza in children: fever (OR 2.849, 95% CI 1.931–8.722), cough (OR 1.99, 95% CI 1.512–3.643), diarrhea (OR 2.100, 95% CI 2.040–3.25) and respiratory disease (OR 3.269, 95% CI 2.128–12.624). In adults, the strongest clinical predictor was fever (OR 2.80, 95% CI 1.025–3.135) followed by cough (OR 1.431, 95% CI 1.032–2.815). In the second instance, patients were separated into two groups: SARI 326 (26%) and ILI 917 (74%) cases. Male to female ratio was 1.41∶1.12 for SARI and 2∶1.5 for ILI cases. Chi-square test showed that fever, cough and sore throat were significant factors for A(H1N1)pdm09 infections (p = 0.008). Conclusion Studies in a primary care setting should be encouraged focused on patients with influenza-like illness to develop sensitive clinical case definition that will help to improve accuracy of detecting influenza infections. Formulation of a standard “one size fits all” case definition that best correlates with influenza infections can help guide decisions for additional diagnostic testing and also discourage unjustified antibiotic prescription and usage in clinical practice.
A Probabilistic Approach to Uncovering Attributed Graph Anomalies

Uncovering subgraphs with an abnormal distribution of attributes reveals much insight into network behaviors. For example in social or communication networks, diseases or intrusions usually do not propagate uniformly, which makes it critical to find anomalous regions with high concentrations of a specific disease or intrusion. In this paper, we introduce a probabilistic model to identify anomalous subgraphs containing a significantly different percentage of a certain vertex attribute, such as a specific disease or an intrusion, compared to the rest of the graph. Our framework, gAnomaly, models generative processes of vertex attributes and divides the graph into regions that are governed by background and anomaly processes. Two types of regularizers are employed to smoothen the regions and to facilitate vertex assignment. We utilize deterministic annealing EM to learn the model parameters, which is less initialization-dependent and better at avoiding local optima. In order to find fine-grained anomalies, an iterative procedure is further proposed. Experiments show gAnomaly outperforms a state-of-the-art algorithm at uncovering anomalous subgraphs in attributed graphs.
Scan chain fault identification using weight-based codes for SoC circuits

Recently, it has been observed that embedded cores in a high-speed SoC circuit have the problem of broken scan chains that cannot shift properly. Also, scan chain intermittent faults caused by hold-time violations and crosstalk noises are pervasive. In this research, an efficient method is proposed to identify the faulty scan chain(s) at the core level. That is, the core where the scan chain is defective can be identified, even if the scan chain is broken. The result can be used to tune up the fabrication process or to guide the fine-grained scan cell identification process. Here, weight-based m-out-of-n codes, which can generate a large number of codewords, with small hardware overhead and high fault detection capability are used to generate the scan chain diagnostic patterns for permanent (and possibly intermittent) faults. An efficient codeword generation method is proposed to maximize the number of codewords, minimize the aliasing probabilities and test application cost. The idea of multiple m-out-of-n codes is also proposed to guarantee that sufficient number of codewords are generated to perturb the scan chains and the associated combinational circuits. Simulation results demonstrate the feasibility of the proposed method.
Binary local descriptors based on robust hashing

A robust hash, or content-based fingerprint, is a succinct representation of the perceptually most relevant parts of a multimedia object. A key requirement of fingerprinting is that elements with perceptually similar content should map to the same fingerprint, even if their bit-level representations are different. In this work we focus on the construction of discriminative binary local descriptors exploiting a combination of content-based fingerprinting techniques and computationally efficient filters (box filters, Haar-like features, etc.) applied to image patches. In particular, we define a possibly large set of filters and iteratively select the most discriminative ones resorting to boosting techniques. The output values of the filtering process are quantized to one bit, leading to a very compact binary descriptor. Preliminary results show that such descriptor leads to compelling results, outperforming SIFT in terms of truepositive / false-positive rate when using as few as 64 bits.