Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Climate Change on River flow Stochastic Approach

One enduring objective in the scientific community has been to understand how climate change impacts the distribution of river flows. In this paper, we explore the impact of this phenomenon on the river flow levels of the Arkansas River in the state of Colorado. Changes in monthly flow regimes were projected and aggregated to decadal time scale using two future climate scenarios. To achieve this, a neural network was employed to map the region, and from this, the relationship between streamflow and accumulated snow and temperature was analyzed and used to derive the streamflow projections. Streamflow projections for the April-September period in the Arkansas River were analyzed and the results show that river flow increases following the increase in precipitation and temperature regimes throughout the river basin. The historical peak flow in June shifted to occur in April. Frequency analyses of flow show that the any flow in the months April-July would be exceeded more frequently in the future. The percentage change in exceedance for each month will vary – with a substantial difference for April-July, a minor change for the month of August, and almost no change at all in September.
IMIAD: Intelligent Malware Identification for Android Platform

Android malware applications and their detection have been under study by security experts for quite some time, but it gained special attention since the ever-growing use of smartphones. Normally, two methods have been commonly used for their identification. One, in which the code and information flow are analyzed is called the static analysis, whereas, in dynamic analysis, malware behaviour is over served at runtime (by executing it in a sandbox environment). It has been observed that both techniques when used separately, fail to identify all the malware, and, an analysis based on this, fail to achieve good accuracy. There is a need to make use of both these strategies for malware identification, so, if any malignant application identification fails during the static analysis, it gets caught during the dynamic one. Though researchers have used a combination of these two approaches and proposed different malware detection strategies, however, to the best of our knowledge none of them has examined the consent model associated with the applications intent in combination with others. Keeping this observation in mind, our proposed technique is a hybrid approach, based on applications intent, its permissions, static and dynamic data. Our supervised learning-based approach results have shown m 96% accuracy in detecting malware applications using gradient boosting classifier
Properties of the Conformal CSCMR System

In this paper, the evolution of Conformal Strongly Coupled Magnetic Resonance (CSCMR) systems is presented. Such systems are highly efficient and misalignment insensitive. The design and miniaturization of these systems is presented here. The performance of CSCMR systems is validated using simulations and measurements.
Prevalence of Bartonella henselae Antibody in Florida Panthers

Serum samples from 28 free-ranging Florida panthers (Puma concolor coryi) and seven mountain lions from Texas (P. concolor stanleyana) living in south Florida (USA) between 1997 to 1998 were tested for antibodies to Bartonella henselae. Twenty percent (7/35) of the samples were reactive to B. henselae antisera with a subspecies prevalence of 18% (5/ 28) for Florida panthers and 28% (2/7) for cougars from Texas (USA). There was not a significant sex related difference in infection rates among the Florida panthers. Antibody prevalence was higher in panthers <2-yr of age (40%) compared to panthers >2-yr (13%). Compared to studies of antibody prevalence in mountain lions (P. concolor) from California (USA), overall seroprevalence was lower as was prevalence in panthers >2-yr-old. However, the seroprevalence in animals <2-yr from southern Florida was similar to prevalences reported in mountain lions or domestic felids in California.
Modeling and Comparison of Delay and Energy Cost of IoT Data Transfers

Communication is often considered as the most costly component of a wireless sensor node. As a result, a variety of technologies and protocols aim to reduce the energy consumption for the communication especially in the Internet of Things context. In order to select the best suitable technology for a given use case, a tool that allows the comparison of these options is needed. The goal of this paper is to introduce a new modular modeling framework that enables a comparison of various technologies based on analytical calculations. We chose to model the cost for a single data transfer of arbitrary application data amounts in order to provide flexibility regarding the data amount and traffic patterns. The modeling approach covers the stack traversal of application data and thus in comparison to other approaches includes the required protocol overhead directly. By applying our models to different data amounts, we are able to show tradeoffs between various technologies and enable comparisons for different scenarios. In addition, our results reveal the impact of design decisions that can help to identify future development challenges.
Evaluations of tear protein markers in dry eye disease: repeatability of measurement and correlation with disease.

PURPOSE We characterized tear protein markers in dry eye disease (DED). METHODS In this prospective study, based on the ocular surface disease index (OSDI) and corneal staining (CS), 95 DED patients (OSDI ≥13) with increasing CS were enrolled into 3 severity groups: DE1 (CS <4), DE2 (CS 4-7), and DE3 (CS >7), while 25 asymptomatic subjects with no CS were enrolled into the control group (OSDI <13 and CS = 0). Tear fluid was collected at day 0 and day 7 visits, and concentrations of 43 protein markers were measured by multiplexed immunoassay. RESULTS We analyzed 22 control and 80 DED subjects. Among 33 markers detectable, good inter-visit repeatability was observed with 25 markers, with intraclass correlation coefficients (ICC) ranging from 0.85-0.60; ICCs were <0.60 in the other 8. Correlation with clinical measures was found with two markers, with absolute partial correlation coefficients >0.40: Interleukin-1 receptor antagonist (IL-1Ra) and IL-8. IL-1Ra and IL-8 correlated with conjunctival staining (0.43, P < 0.001 and 0.35, P < 0.01, respectively), and with Schirmer test (-0.58 and -0.42, P < 0.001). IL-1Ra and IL-8 in DE3 were 4.4- and 2.1-fold higher than in DE1 (P = 0.0001 and 0.0007), and 1.9- and 1.6-fold higher than in DE2 (P = 0.022 and 0.017). IL-1Ra in DE2 was 2.3-fold higher than in DE1 (P = 0.038). CONCLUSIONS Tear levels of many immune mediators were highly repeatable between visits in DED. Among them, IL-1Ra and IL-8 were associated with clinical signs and disease severity defined by corneal staining.
A Network Planning Approach for Truck Restriction in Heterogeneous Traffic

Restriction of the movement of heavy-trucks in a transportation network is a commonly used strategy to mitigate traffic congestion and pollution issues, especially in congested urban areas. However, the cost and capacity functions used in the literature are inadequate to describe the traffic dynamics in heterogeneous conditions. This paper proposes a systematic framework with new cost and capacity functions, to identify critical links in a network and to determine the minimum cost truck routes in the network by restricting trucks on identified critical links. A hierarchical mathematical programming framework with integer programming formulations are presented. The capacity and cost functions are derived based on a multiclass model and shockwave analysis to represent realistic traffic flow interactions between the trucks and cars. The model results are validated using VISSIM simulation, which shows that the total delay reduced and the network capacity utilization improved with truck restriction.
Intuitionistic Fuzzy Inference System with Genetic Tuning for Predicting Financial Performance

Intuitionistic fuzzy inference systems are used to model the uncertainty associated with positive and negative information and preferences. Here, we propose a novel intuitionistic fuzzy inference system of the Takagi-Sugeno-Kang type with genetic tuning. A genetic fuzzy apriori algorithm is used to obtain both the set of if-then rules and the initial values of the premise parameters. Then, a genetic algorithm is applied to tune the premise and consequent parameters of the intuitionistic fuzzy inference system. We demonstrate the effectiveness of the proposed system for predicting corporate financial performance and show that the system has higher prediction accuracy than state-of-the-art fuzzy inference systems.
Bit-Flip Algorithm for Successive Cancellation List Decoder of Polar Codes

A successive cancellation list (SCL) decoder with the assistance of a cyclic redundancy check (CRC) can provide competitive decoding performance for polar codes compared with the state-of-the-art codes. In this paper, we adopt a bit-flip algorithm for the CRC-assisted SCL decoder to further improve the error-correcting performance. We first introduce a new bit-flip criterion for the SCL decoder. To support this criterion, we give the metric to identify the positions that need to be flipped. To verify the superiority of the proposed bit-flip criterion, we also consider a kind of SCL-flip decoder whose criterion is very similar with the existing one and we will prove that its performance is worse than the decoder with the proposed bit-flip criterion. The simulation results show that the decoder with the proposed bit-flip criterion outperforms both the standard CRC-assisted SCL decoder and the existing SCL-based bit-flip decoder.
A Robust Method for Hands Gesture Recognition from Egocentric Depth Sensor

We present a method for robust and accurate hand pose recognition from egocentric depth cameras. Our method combines CNN based hand pose estimation and joint locations based hand gesture recognition. In pose estimation stage, we use a hand geometry prior network to estimate the hand pose. In gesture recognition stage, we defined a hand language which based on a set of pre-define basic propositions, obtained by applying four predicate types to the fingers and palm states. The hand language is used to convert the estimated joint location to hand gesture. Our experimental results indicate that the method enables robust and accurate gesture recognition in self-occlusion environment.
Cost/Privacy Co-optimization in Smart Energy Grids

The smart energy grid features real-time monitoring of electricity usage such that it can control the generation and distribution of electricity as well as utilize dynamic pricing in response to the demands. For this purpose, smart metering systems continuously monitor the electricity usage of customers, and report it back to the Utility Provider (UP). This raises privacy concerns regarding the undesired exposure of human activity and time-of-use of home appliances. Photovoltaics (PV) and a residential Electrical Energy Storage (EES) have proven to be effective in mitigating the privacy concerns. However, this comes at several costs: Installation of PV and EES, their subsequent aging and the possibly increased electricity cost. We quantify the trade-off between privacy exposure and financial costs by formulating a stochastic dynamic programming problem. Our analysis shows that i) there is a quantifiable trade-off between the financial cost and privacy leakage, ii) proper control of the system is crucial for both metrics, iii) a strategy solely focusing on privacy results in high financial costs, and iv) that for a typical residential setting, the costs for a trade-off solution lie in the range of 600 US$-1700 US$. As the load flattening has a peak shaving effect desirable for UPs, increasing privacy is mutually beneficial for both, customers and UPs.
Indoor Localization Based on Channel State Information

Indoor localization has been an important area of research for many years. A more recent development in this space is towards device-free localization techniques. We present a thorough survey and results from our attempt to increase the accuracy and robustness relating to the device-free indoor-localization problem. Using WiFi network signals for such localization tasks, almost near-perfect accuracy could be reached. We build on top of two [1] [2] of the recent works that use WiFi Channel State Information (CSI), to test and experiment indoor localization accuracy at room level. Our work evaluates the achievable improvements by experimenting with classical machine learning and deep learning models. We also briefly discuss the instability of CSI data due to drift over time.
A High Capacity and Imperceptible Text Steganography Using Binary Digit Mapping on ASCII Characters

Due to its light and multiplatform feature, plain text is widely used to transmit the information in news and social media online. However, it is vulnerable to attacks (e.g. unauthorized access or misuse of the information where the text is modified for particular purposes). To deal with the problem, secret text (ST) is embedded in overall plain texts appearing as a cover text (CT) so that any changes on CT can be detected. The present study proposes ST embedding method in CT by mapping ST binary digit onto binary digit of CT using ASCII characters-involving spaces, punctuation, and symbols. Prior to embedding process, the ST text was firstly encrypted with a One Time Pad (OTP) into ciphertext and each character was converted into binary number representing 7-bits long. Unlike the ST text, the CT text was immediately converted into 7 bits of binary number. The embedding process was conducted by mapping one bit of ST onto the first bit of CT character containing the same number of bit (e.g. mapping bit 1 of ST character onto the first bit 1 of CT character). Such a process was repeatedly carried out to ensure all bit of ST was completely embedded in CT. The system recorded each bit position as a stego key for any bit of ST had its position on bit of CT. The stego key served as a key to extract ST embedded in CT. The result of embedding process did not change the appearance of CT and therefore the method worked well with hidden information serving as text steganography or as watermark. In short, all CT characters can be used as a medium to hide ST where 1 character of ST required 7 characters of CT. In addition, the stego texts produced appeared identical to CT, as measured in similarity distance with Jaro-Winkler Distance of 1.
Informational needs of liver transplant recipients during a two-year posttransplant period

Objectives To describe the informational needs of liver transplant (LTx) recipients, examine potential differences in informational needs by sociodemographic and clinical variables, and examine informational needs at various time points posttransplant. Methods A descriptive, cross-sectional design was used. Informational needs were assessed by the Informational Needs Questionnaire-liver, a new questionnaire developed to include LTx recipients' perspectives. To examine informational needs at different posttransplant time points, participants were classified into four groups (0–1, 2–4, 5–9, and 10–24 months). Results Participants (159) who were married, single, had higher education, or higher monthly incomes had significantly greater informational needs. Informational needs regarding disease and physical and emotional management remained high after transplant. Four subscales (medication, wound management, diet, and daily and social activities) indicated informational needs were different across time. Participants 2–4 months posttransplant had higher informational needs regarding wound management and daily and social activities. Participants 5–9 months posttransplant had the highest informational needs regarding medication and diet. Discussion Findings indicate informational needs vary among LTx recipients at different posttransplant time points. Marital status, education, and monthly income can influence informational needs. Conclusion Healthcare providers should tailor information given to LTx recipients based on informational needs. Longitudinal studies are needed to confirm changing patterns of informational needs.
Diversity of the C-Terminal Portion of the Biphenyl Dioxygenase Large Subunit

The biphenyl dioxygenase (BPDO) catalyses a stereospecific dioxygenation of biphenyl and analogs of it. Aside from being involved in the destruction and detoxification of toxic pollutants in soil, in the context of the green chemistry concept, this enzyme is a promising biocatalyst to design new more selective and more environmentally friendly approaches to manufacture fine chemicals. At this time, most of our knowledge about the variability of key residues determining the substrate specificity and regiospecificity of the enzyme oxygenase component (BphAE) toward biphenyl analogs and about the effect of altering these residues on catalytic properties is based on investigations made with BphAEs from cultured organisms and engineered enzymes derived from them. The purpose of this work was to examine the diversity of the amino acid sequence patterns of the α subunit (BphA) C-terminal domain deduced from PCR products amplified from DNA extracted from cultured bacteria of various phylogenetic lines and from the soil microflora of PCB-contaminated soils. Of special interest were segments of the C-terminal portion called regions I, III and IV. Altogether, the phylogenetic tree obtained from aligning the deduced amino acid sequences of BphAs C-terminal domain from cultured bacteria belonging to various ecological niches and from uncultured soil bacteria reveals that most of the BphAs were linked to the three clusters of BphAs previously reported. However, few belong to new branches that diverge from the previously known branches showing a high diversity of BphAs in natural environment. Furthermore, data show a wide distribution of BphAs with family linkages that not only crosses bacterial taxonomic frontiers but also ecological niches. Nevertheless, in spite of this divergence, the sequence patterns of regions III and IV amino acids that are known to influence substrate specificity and regiospecificity are rather conserved among BphAs and the pattern was independent of the family cluster to which they belong. In most cases, regions III and IV amino acid patterns are closer to those of Pseudomonas pseudoalcaligenes KF707 BphA1 than to the most versatile Burkholderia xenovorans LB400 BphA. This might suggest that the PCB-degrading potency of soil bacteria is closer to the one observed for KF707 BphAE than from LB400 BphAE. However, the fact that among less than 20 PCR products amplified from soil DNA that we have sequenced, one of them was very homologous to that of LB400 BphA and in addition, residues 335 and 336 of LB400 were replaced by residues that previous enzyme engineering had shown to extend the range of PCB substrate used by the enzyme strongly suggest that PCB-degrading bacteria are evolving in soil to optimize their PCB-degrading capacity.
SAID: A Supergate-Aided Logic Synthesis Flow for Memristive Crossbars

A Memristor is a two-terminal device that can serve as a non-volatile memory element with built-in logic capabilities. Arranged in a crossbar structure, memristive arrays allow to represent complex Boolean logic functions that adhere to the logic-in-memory paradigm, where data and logic gates are glued together on the same piece of hardware. Needless to say, novel and ad-hoc CAD solutions are required to achieve practical and feasible hardware implementations. Existing techniques aim at optimal mapping strategies that account for Boolean logic functions described by means of 2-input NOR and NOT gates, thus overlooking the optimization capabilities that a smart and dedicated technology-aware logic synthesis can provide. In this paper, we introduce a novel library-free supergate-aided (SAID) logic synthesis approach with a dedicated mapping strategy tailored on MAGIC crossbars. Supergates are obtained with a Look-Up Table (LUT)-based synthesis that splits a complex logic network into smaller Boolean functions. Those functions are then mapped on the crossbar array as to minimize latency. The proposed SAID flow allows to (i) maximize supergate-level parallelism, thus reducing the total number of computing cycles, and (ii) relax mapping constraints, allowing an easy and fast mapping of Boolean functions on memristive crossbars. Experimental results obtained on several benchmarks from ISCAS’85 and IWLS’93 suites demonstrate that our solution is capable to outperform other state-of-the-art techniques in terms of speedup (3.89× in the best case), at the expense of a very low area overhead.
Conflict-Triggered Goal Shielding

Action control in a changing environment requires that one shield current goals from distracting information (goal shielding) and at the same time monitor the environment for potentially significant stimuli that may afford a goal switch (background monitoring). Response conflicts modulate the balance between goal shielding and background monitoring, as indicated by reduced susceptibility to interference after response conflicts. Such conflict-adaptation effects have been attributed to enhanced recruitment of cognitive control on trials following conflicts. Here we show that conflict triggers increased goal shielding on the conflict trial itself. Subjects performed a spatial compatibility task during which they had to notice rare prospective memory cues. Such cues were overlooked more often on conflict trials than on nonconflict trials, a result indicating that shielding of the current goal and inhibition of distractors were increased on the current trial when it involved a response conflict. Thus, evidence for enhanced recruitment of control following conflict may partly reflect aftereffects of goal shielding on the conflict trial itself.
Efficacy and safety of latanoprost versus pilocarpine/timolol maleate fixed combination in patients with primary open‐angle glaucoma or ocular hypertension

Purpose: This study aimed to compare the safety and effect on intraocular pressure (IOP) of latanoprost given every evening versus pilocarpine/timolol maleate fixed combination (PTFC) given twice daily in patients with primary open‐angle glaucoma (POAG) or ocular hypertension (OH).
On the Effect of Dissipation and Nonlocality on Unidirectional and Topological Surface Plasmon-Polaritons

Unidirectional surface plasmon polaritons (SPPs) on nonreciprocal material platforms are currently the subject of significant interest. In this abstract, we revisit this exciting topic, discussing the role of the nonlocal response of a magnetized plasmonic material. Our analytical calculations and frequency-domain finite-element simulations confirm that a nonlocal correction in the material model implies the absence of purely unidirectional SPP modes below the plasma frequency. However, we also show that, depending on the considered configuration, the presence of even moderate levels of loss (absorption or radiation) can practically restore the unidirectionality of this mode. Our findings have important implications in the context of nonreciprocal and topological electromagnetic systems.