Miracle-dz/UniFAR-FTUs huggingface dataset:
A Neutral-Type Delayed Projection Neural Network for Solving Nonlinear Variational Inequalities

A neutral-type delayed projection neural network is proposed to deal with nonlinear variational inequalities. Compared with the existing delayed neural networks for linear variational inequalities, the proposed approach apparently has the larger application domain. By the theory of functional differential equation, a delay-dependent sufficient stability condition is derived. This stability condition is easily checked, and can guarantee that the proposed neural network is convergent to the solution of nonlinear variational inequality problem exponentially, which improves the existing stability criteria for the neutral-type delayed neural network. Moreover, many related problems, such as the projection equation and optimization problems, can also be dealt with by the proposed method. Finally, simulation examples are given to illustrate the satisfactory performance of the proposed method.
Fundamental Limitations of Emission-Line Spectra as Diagnostics of Plasma Temperature and Density Structure

We discuss the problem of determining plasma structure from optically thin emission lines whose emission coefficients and frequency-integrated intensities are dependent on temperature T and electron density n. We cast the problem into the inverse form discussed by Hubeny & Judge (1995). Three properties of the kernels in the integral equations lead to fundamental limitations in trying to determine the source term μ(T, n), the “emission measure differential in temperature and density,” from a set of emission-line intensities. First, the kernels are rather weakly dependent on n. Second, they have asymptotically identical dependencies on n. The inverse problem is therefore very poorly conditioned in the density dimension. Third, the kernels cannot (and may never) be calculated with an accuracy better than ±10%. These properties set limits on the accuracy of all solutions, independent of the accuracy of observed line intensities. This concurs with earlier but less general work by Brown et al. (1991). We try to determine solutions for μ(T, n), using specific target sources and numerical algorithms. Using realistic uncertainties, calculations indicate that meaningful inverse solutions for μ(T, n) cannot be obtained owing to the severe propagation of kernel errors, irrespective of the quality of observational data. Solutions for the “emission measure differential in temperature” ξ(T) = ∫ μ(T, n)dn are more robust against instabilities driven by poor conditioning. Since traditional “emission-line diagnostic ratios” can only be defined through μ(T, n) (or some generalization thereof), our analysis casts doubt on the meaning of plasma properties derived from such line ratios, and illustrates the severe nonuniqueness of any equivalent “inverse” solution. This work may be important for studying a wide variety of atomic and ionic emission-line spectra, including work with instruments on SOHO and the Hubble Space Telescope.
Drinking water treatment with a commercial preparation of a concentrated Lactobacillus culture for broiler chickens.

Three hundred male broiler chicks were used to determine the effects of supplying Lactobacillus in the drinking water. The product used, Biomax 40TM, was a fresh-frozen, pure culture of Lactobacillus containing 40 X 10(9) cfu/ml. Water treatments consisted of continuous lactobacilli dosing (CD) and skip-a-day lactobacilli dosing (SAD). A control group (C) received no lactobacilli. Each treatment and control contained two pens of 50 chicks each and were fed for a duration of 7 weeks. At the termination of the experiment, weights of the wet viscera, and wet and dry small intestines of the broilers revealed no significant differences between treatments and control. Surface pH readings taken from crop and duodenum showed that there was no significant difference (P greater than .05). Microbiology performed on duodenal contents revealed higher numbers of lactobacilli for CD and SAD broilers than for C broilers. The liver biotin contents of the lactobacilli-treated broilers were not significantly different from those of the controls. Body weights were not changed by either treatment, although they were greater for the CD broilers than for the SAD broilers. No difference was observed in feed conversion (feed/gain).
Image encryption based on compressed sensing and blind source separation

A novel image encryption scheme based on compressed sensing and blind source separation is proposed in this work, where there is no statistical requirement to plaintexts. In the proposed method, for encryption, the plaintexts and keys are mixed with each other using a underdetermined matrix first, and then compressed under a project matrix. As a result, it forms a difficult underdetermined blind source separation (UBSS) problem without statistical features of sources. Regarding the decryption, given the keys, a new model will be constructed, which is solvable under compressed sensing (CS) frame. Due to the usage of CS technology, the plaintexts are compressed into the data with smaller size when they are encrypted. Meanwhile, they can be decrypted from parts of the received data packets and thus allows to lose some packets. This is beneficial for the proposed encryption method to suit practical communication systems. Simulations are given to illustrate the availability and the superiority of our method.
A weak-illumation image enhancement method uisng homomorphic filter and image fusion

In this paper, an image enhancement method for weak-illumination image is studied by using homomorphic filter and image fusion. First, the discrete-cosine-transform (DCT) based homomorphic filtering technique is used to enhance image without changing hue and saturation. Because it is not easy to determine suitable filter parameters such that image quality is good for all objects, an image fusion method is then developed to combine several enhanced images with different exposures to get the final result. Finally, a back-lighting image is used to show the effectiveness of the proposed method and the comparisons with traditional methods are made.
Effect of feed allowance during rearing and breeding on female broiler breeders. 2. Ovarian morphology and production.

The influence of feed allowance during rearing (4 to 18 wk) and breeding (18 to 62 wk) on ovarian morphology and egg production was examined. During rearing, beginning at 4 wk of age, 400 Indian River pullets that had been full-fed from 1 day of age either continued to be full-fed (F, n = 200) or were feed restricted (R, n = 200), following commercial practice. At 18 wk of age, 100 birds (within +15% of the mean BW) in each of F and R rearing groups were further assigned to be full-fed (n = 50) or feed restricted (n = 50) during breeding. Thus, based on feed allowance during rearing and breeding, four treatment groups were formed (FF, FR, RF, and RR). Feed restriction during rearing significantly delayed oviduct development and age at sexual maturity (age at first egg). Compared with feed restriction during both rearing and breeding (RR), ad libitum feeding beginning at 18 wk of age (RF) significantly increased the weight of the ovary and the number of large follicles at sexual maturity but did not significantly affect the age at sexual maturity. Feed restriction during rearing, breeding, or both significantly reduced the incidence of erratic ovipositions, defective eggs, and multiple ovulations. The incidence of erratic ovipositions was positively correlated (r = .692, P less than or equal to .001) with the laying of soft-shelled and shell-less eggs and negatively correlated (r = -.508, P less than or equal to .001) with the production of settable eggs to 62 wk of age. Compared with ad libitum feeding, controlled feeding during breeding significantly improved both settable and total egg production. Among the four feeding regimens, Treatment RR resulted in the highest fertility and hatchability.
Patient Preferences for Follow-up After Recent Excision of a Localized Melanoma

Importance The standard model of follow-up posttreatment of localized melanoma relies on clinician detection of recurrent or new melanoma, through routinely scheduled clinics (clinician-led surveillance). An alternative model is to increase reliance on patient detection of melanoma, with fewer scheduled visits and increased support for patients’ skin self-examination (SSE) (eg, using smartphone apps to instruct, prompt and record SSE, and facilitate teledermatology; patient-led surveillance). Objective To determine the proportion of adults treated for localized melanoma who prefer the standard scheduled visit frequency (as per Australian guideline recommendations) or fewer scheduled visits (adapted from the Melanoma Follow-up [MELFO] study of reduced follow-up). Design, Setting, and Participants This survey study used a telephone interview for surveillance following excision of localized melanoma at an Australian specialist center. We invited a random sample of 400 patients who had completed treatment for localized melanoma in 2014 to participate. They were asked about their preferences for scheduled follow-up, and experience of follow-up in the past 12 months. Those with a recurrent or new primary melanoma diagnosed by the time of interview (0.8-1.7 years since first diagnosis) were asked about how it was first detected and treated. SSE practices were also assessed. Main Outcomes and Measures Proportion preferring standard vs fewer scheduled clinic visits, median delay between detection and treatment of recurrent or new primary melanoma, and SSE practices. Results Of the 262 people who agreed to be interviewed, the mean (SD) age was 64.3 (14.3) years, and 93 (36%) were women. Among the 230 people who did not have a recurrent or new primary melanoma, 149 vs 81 preferred the standard vs fewer scheduled clinic visits option (70% vs 30% after adjusting for sampling frame). Factors independently associated with preferring fewer visits were a higher disease stage, melanoma on a limb, living with others, not having private health insurance, and seeing a specialist for another chronic condition. The median delay between first detection and treatment of recurrent or new primary melanoma was 7 and 3 weeks, respectively. Only 8% missed a scheduled visit, while 40% did not perform SSE or did so at greater than 3-month intervals. Conclusions and Relevance Some patients with melanoma may prefer fewer scheduled visits, if they are supported to do SSE and there is rapid clinical review of anything causing concern (patient-led surveillance).
Hydrolysates of Fish Skin Collagen: An Opportunity for Valorizing Fish Industry Byproducts

During fish processing operations, such as skinning and filleting, the removal of collagen-containing materials can account for up to 30% of the total fish byproducts. Collagen is the main structural protein in skin, representing up to 70% of dry weight depending on the species, age and season. It has a wide range of applications including cosmetic, pharmaceutical, food industry, and medical. In the present work, collagen was obtained by pepsin extraction from the skin of two species of teleost and two species of chondrychtyes with yields varying between 14.16% and 61.17%. The storage conditions of the skins appear to influence these collagen extractions yields. Pepsin soluble collagen (PSC) was enzymatically hydrolyzed and the resultant hydrolysates were ultrafiltrated and characterized. Electrophoretic patterns showed the typical composition of type I collagen, with denaturation temperatures ranged between 23 °C and 33 °C. In terms of antioxidant capacity, results revealed significant intraspecific differences between hydrolysates, retentate, and permeate fractions when using β-Carotene and DPPH methods and also showed interspecies differences between those fractions when using DPPH and ABTS methods. Under controlled conditions, PSC hydrolysates from Prionace glauca, Scyliorhinus canicula, Xiphias gladius, and Thunnus albacares provide a valuable source of peptides with antioxidant capacities constituting a feasible way to efficiently upgrade fish skin biomass.
How patients’ experiences of respiratory tract infections affect healthcare-seeking and antibiotic use: insights from a cross-sectional survey in rural Anhui, China

Objective To investigate the occurrence of reported respiratory tract infection (RTI) symptoms and their effects on use of self and professional care among patients in the community. Design A cross-sectional retrospective household survey. Setting 12 administrative villages from rural Anhui, China. Participants 2160 rural adult residents aged ≥18 years registered as rural residents and actually living in the sampled villages when this study was conducted. Method The respondents were recruited using stratified-clustered randomised sampling. A structured questionnaire was deployed to solicit information about social demographics, symptoms of last RTI and healthcare-seeking following the RTI. Descriptive analyses were performed to investigate the reported symptoms, and multivariate logistic regression models were developed to identify relationships between number of concurrent symptoms and healthcare-seeking and antibiotics use. Results A total of 1968 residents completed the survey, resulting in a response rate of 91.1%. The number of concurrent symptoms showed a clear increasing trend with seeking help from clinics and being prescribed antibiotics. Multivariate regression revealed statistically significant associations between the following: (a) visiting clinics and education (OR=0.790), sore throat (OR=1.355), cough (OR=1.492), shortness of breath (OR=1.707) and fever (OR=2.142); (b) buying medicine from shops without prescription and education (OR=1.230) and cough (OR=1.452); (c) getting antibiotics at clinics and sore throat (OR=2.05) and earache and/or tinnitus (OR=4.884); and (d) obtaining antibiotics at medicine shops and productive cough (OR=1.971). Conclusions Reported RTI symptoms play an important role in shaping both patient- and doctor-led responses.
Machine learning on merging static and dynamic features to identify malicious mobile apps

The amount of Android system-targeted malware has increased dramatically in recent years, and Android has been the focus of far more malware targeting than other mobile operating systems. In order to reduce the hazards of malware, this paper proposes a malware detection system with static and dynamic app features. In terms of the static features, the permissions, native-permissions, function and priority of an app are extracted as the base of analysis. In terms of the dynamic feature, the app is executed in a sandbox emulator, and then log files are analyzed to identify behaviors that help judgment, such as sending short messages without permission, modifying system files or reading personal data. This system extracts the static and dynamic features of an app, which are then merged before the weights are adjusted appropriately. Finally, Weka is used for training to obtain the detection module. According to the experiment, an unknown malicious act is evaluated using tenfold cross validation; the proposed system achieves a 97.4% accuracy.
A Data Set of Human Body Movements for Physical Rehabilitation Exercises

The article presents University of Idaho – Physical Rehabilitation Movement Data (UI-PRMD) — a publically available data set of movements related to common exercises performed by patients in physical rehabilitation programs. For the data collection, 10 healthy subjects performed 10 repetitions of different physical therapy movements, with a Vicon optical tracker and a Microsoft Kinect sensor used for the motion capturing. The data are in a format that includes positions and angles of full-body joints. The objective of the data set is to provide a basis for mathematical modeling of therapy movements, as well as for establishing performance metrics for evaluation of patient consistency in executing the prescribed rehabilitation exercises.
ProteinAC: a frequency domain technique for analyzing protein dynamics

It is widely believed that the interactions of proteins with ligands and other proteins are determined by their dynamic characteristics as opposed to only static, time-invariant processes. We propose a novel computational technique, called ProteinAC (PAC), that can be used to analyze small scale functional protein motions as well as interactions with ligands directly in the frequency domain. PAC was inspired by a frequency domain analysis technique that is widely used in electronic circuit design, and can be applied to both coarse-grained and all-atom models. It can be considered as a generalization of previously proposed static perturbation-response methods, where the frequency of the perturbation becomes the key. We discuss the precise relationship of PAC to static perturbation-response schemes. We show that the frequency of the perturbation may be an important factor in protein dynamics. Perturbations at different frequencies may result in completely different response behavior while magnitude and direction are kept constant. Furthermore, we introduce several novel frequency dependent metrics that can be computed via PAC in order to characterize response behavior. We present results for the ferric binding protein that demonstrate the potential utility of the proposed techniques.
Designing and fabricating mechanical automata from mocap sequences

Mechanical figures that mimic human motions continue to entertain us and capture our imagination. Creating such automata requires expertise in motion planning, knowledge of mechanism design, and familiarity with fabrication constraints. Thus, automaton design remains restricted to only a handful of experts. We propose an automatic algorithm that takes a motion sequence of a humanoid character and generates the design for a mechanical figure that approximates the input motion when driven with a single input crank. Our approach has two stages. The motion approximation stage computes a motion that approximates the input sequence as closely as possible while remaining compatible with the geometric and motion constraints of the mechanical parts in our design. Then, in the layout stage, we solve for the sizing parameters and spatial layout of all the elements, while respecting all fabrication and assembly constraints. We apply our algorithm on a range of input motions taken from motion capture databases. We also fabricate two of our designs to demonstrate the viability of our approach.
Compositional shifts in root-associated bacterial and archaeal microbiota track the plant life cycle in field-grown rice

Bacterial communities associated with roots impact the health and nutrition of the host plant. The dynamics of these microbial assemblies over the plant life cycle are, however, not well understood. Here, we use dense temporal sampling of 1,510 samples from root spatial compartments to characterize the bacterial and archaeal components of the root-associated microbiota of field grown rice (Oryza sativa) over the course of 3 consecutive growing seasons, as well as 2 sites in diverse geographic regions. The root microbiota was found to be highly dynamic during the vegetative phase of plant growth and then stabilized compositionally for the remainder of the life cycle. Bacterial and archaeal taxa conserved between field sites were defined as predictive features of rice plant age by modeling using a random forest approach. The age-prediction models revealed that drought-stressed plants have developmentally immature microbiota compared to unstressed plants. Further, by using genotypes with varying developmental rates, we show that shifts in the microbiome are correlated with rates of developmental transitions rather than age alone, such that different microbiota compositions reflect juvenile and adult life stages. These results suggest a model for successional dynamics of the root-associated microbiota over the plant life cycle.
The contribution of unsafe blood transfusion to human immunodeficiency virus incidence in sub‐Saharan Africa: reexamination of the 5% to 10% convention

Historical estimates have attributed 5% to 10% of new human immunodeficiency virus (HIV) infections in sub‐Saharan Africa (SSA) to unsafe blood transfusions. Although frequently cited, the validity of this statistic is uncertain or outdated. Recent estimates suggest blood transfusion's contribution to new HIV infections in the region may be much lower.
Analysis of Software Countermeasures for Whitebox Encryption

Whitebox cryptography aims to ensure the security of cryptographic algorithms in the whitebox model where the adversary has full access to the execution environment. To attain security in this setting is a challenging problem: Indeed, all published whitebox implementations of standard symmetric-key algorithms such as AES to date have been practically broken. However, as far as we know, no whitebox implementation in real-world products has suffered from a key recovery attack. This is due to the fact that commercial products deploy additional software protection mechanisms on top of the whitebox implementation. This makes practical attacks much less feasible in real-world applications. There are numerous software protection mechanisms which protect against standard whitebox attacks. One such technique is control flow obfuscation which randomizes the order of table lookups for each execution of the whitebox encryption module. Another technique is randomizing the locations of the various Look up tables (LUTs) in the memory address space. In this paper we investigate the effectiveness of these countermeasures against two attack paradigms. The first known as Differential Computational Analysis (DCA) attack was developed by Bos, Hubain, Michiels and Teuwen in CHES 2016. The attack passively collects software execution traces for several plaintext encryptions and uses the collected data to perform an analysis similar to the well known differential power attacks (DPA) to recover the secret key. Since the software execution traces contain time demarcated physical addresses of memory locations being read/written into, they essentially leak the values of the inputs to the various LUTs accessed during the whitebox encryption operation, which as it turns out leaks sufficient information to perform the power attack. We found that if in addition to control flow obfuscation, one were to randomize the locations of the LUTs in the memory, then it is very difficult to perform the DCA on the resultant system using such table inputs and extract the secret key in reasonable time. As an alternative, we investigate the version of the DCA attack which uses the outputs of the tables instead of the inputs to mount the power analysis attack. This modified DCA is able to extract the secret key from the flow obfuscated and location randomized versions of several whitebox binaries available in crypto literature. We develop another attack called the Zero Difference Enumeration (ZDE) attack. The attack records software traces for several pairs of strategically selected plaintexts and performs a simple statistical test on the effective difference of the traces to extract the secret key. We show that ZDE is able to recover the keys of whitebox systems. Finally we propose a new countermeasure for protecting whitebox binaries based on insertion of random delays which aims to make both the ZDE and DCA attackspractically difficult by adding random noise in the information leaked to the attacker.
Quadrature-based features for kernel approximation

We consider the problem of improving kernel approximation via randomized feature maps. These maps arise as Monte Carlo approximation to integral representations of kernel functions and scale up kernel methods for larger datasets. Based on an efficient numerical integration technique, we propose a unifying approach that reinterprets the previous random features methods and extends to better estimates of the kernel approximation. We derive the convergence behaviour and conduct an extensive empirical study that supports our hypothesis.