Miracle-dz/UniFAR-FTUs huggingface dataset:
Filtration Performances of Different Polysaccharides in Microfiltration Process

Membrane technology has been widely applied for water treatment, while membrane fouling still remains a big challenge. The polysaccharides in extracellular polymeric substances (EPS) have been known as a significant type of foulant due to their high fouling propensity. However, polysaccharides have many varieties which definitely behave differently in membrane filtration. Therefore, in this study, different polysaccharides alginate sodium and xanthan gum were chosen to study their effects on membrane fouling in a wide concentration range. The results demonstrated that the filtration behaviors of alginate sodium and xanthan gum were completely different, which was due to their different molecular structures. Alginate had a small molecular weight and it was easy for alginate to penetrate membrane pores resulting in pore blocking. A series of concentrations of alginate including 5 mg/L, 10 mg/L, 20 mg/L, 30 mg/L, 40 mg/L, and 50 mg/L were examined and it was found that the permeate flux decline highly depended on the level of alginate in the feed water. While for the filtration of xanthan gum, the same concentration of xanthan gum led to more serious fouling than that observed in alginate, which might be due to its large molecule. In addition, calcium chloride was added in the solutions of both alginate and xanthan gum to examine the influence of a divalent cation on polysaccharide fouling. A “unimodal” peak can be observed in the fouling propensity caused by Ca2+ and alginate with increasing the concentration of alginate. Such a phenomenon was not found in the fouling of xanthan gum and Ca2+ led to more serious fouling for all concentrations of xanthan gum. In light of this, this study gave new insights into the fouling propensities of different polysaccharides.
Advanced Support Vector Machine- (ASVM-) Based Detection for Distributed Denial of Service (DDoS) Attack on Software Defined Networking (SDN)

Software Defined Networking (SDN) has many advantages over a traditional network. The great advantage of SDN is that the network control is physically separated from forwarding devices. SDN can solve many security issues of a legacy network. Nevertheless, SDN has many security vulnerabilities. The biggest issue of SDN vulnerabilities is Distributed Denial of Service (DDoS) attack. The DDoS attack on SDN becomes an important problem, and varieties of methods had been applied for detection and mitigation purposes. The objectives of this paper are to propose a detection method of DDoS attacks by using SDN based technique that will disturb the legitimate user's activities at the minimum and to propose Advanced Support Vector Machine (ASVM) technique as an enhancement of existing Support Vector Machine (SVM) algorithm to detect DDoS attacks. ASVM technique is a multiclass classification method consisting of three classes. In this paper, we can successfully detect two types of flooding-based DDoS attacks. Our detection technique can reduce the training time as well as the testing time by using two key features, namely, the volumetric and the asymmetric features. We evaluate the results by measuring a false alarm rate, a detection rate, and accuracy. The detection accuracy of our detection technique is approximately 97% with the fastest training time and testing time.
The Paradox of Religious Education in Secondary School Curriculum: An Exploratory Study in Mara Region, Tanzania

The present study attempted to investigate on the paradox of Religious Education in Mara Region through qualitative approach. Twelve schools composed the population and purposive sampling came up with 17 students and 4 teachers from three schools to release information through Focus Group Discussion and Interview Schedule. Expert judgment established validity of research instruments. To maintain ethical considerations, anonymity, confidentiality and privacy of respondents were maximized during data collection. The study established that Divinity Subject has peculiar features which are not found in other academic subjects. Failure to integrate Religious Education is influenced by scarcity of teachers, lack of textbooks and non-availability of syllabus to guide the teaching and learning of the subject. Excluding Divinity in selection for tertiary education leads students and teachers to disregard the subject regardless of its benefits. Researchers recommend that Secondary Schools in Mara Region should integrate Religious Education by making it compulsory. Availability of teachers for CRE and good supply of textbooks and syllabus must be ensured in order to enhance proper learning. Divinity should be considered in selection for tertiary education in order to encourage teachers and students to teach and learn the subject. Finally, the government should make efforts to prepare experts to teach Christian Religious Education.
Shannon Limit of Coding in Wireless Communication

A limit SNR(signal noise ratio) -1.6dB has been derived in continuous AWGN channel by shannon theorem. In this paper we study the channel capacity and limit SNR by series representation unlike iteration method for BI-AWGN(discrete binary input, continuous output) and rayleigh channel in BPSK modulation. The limit SNR is obtained under the help of Cesαro series summation rule. We figure out that BI-AWGN and rayleigh channel with (channel state information)CSI behave the same in limit SNR in terms of R → 0 and P → 0. For rayleigh channel without CSI, We solve it approximately by series expanded in R → 0 and an expression of capacity behaves more simple than the two others derived before.
Catastrophizing and Pain

Catastrophizing is a clinical-psychological phenomenon, comparatively frequently encountered in clinical practice. The idea that it is a predictor of pain and it is not always related to the expressiveness of the affective disorder has been more and more convincingly maintained in the last few years. The recognition of catastrophizing and the appropriate therapeutic behavior by psychologists, neurologists, anesthesiologists and others are a prerequisite for the successful treatment of patients with this kind of problem.
Testosterone therapy may reduce prostate cancer risk due to testosterone deficiency at a young age via stabilizing serum testosterone levels

Abstract Objectives: To investigate whether testosterone replacement therapy (TRT) reduces prostate cancer (PCa) risk via stabilizing serum testosterone (T) levels beyond simply elevating serum T levels and whether TRT reduces PCa risk due to low serum T levels at a young age. Methods: We analyzed data of 776 hypogonadal men from a urology center in Bremerhaven, Germany through 2004–2016 to investigate whether the TRT group has more stable T levels and whether TRT can reduce the risk of PCa due to low serum T levels at an early age. We derived an index, Maximum Decline of T Relative to Baseline (MDRB), to describe the magnitude of T declines and variations over time. Results: We found the TRT group has more stable serum T levels (e.g. smaller drop-offs) during the follow-up period as compared to the non-TRT group, and the mean of MDRB is significantly higher in the untreated group (1.553 nmol/L VS 0.013 nmol/L; p-value < .001). TRT significantly reduces the risk of PCa associated with T deficiency at a young age (p-value = .00087). Conclusions: TRT may reduce PCa risk via maintaining serum T levels within individual’s normal range; T surveillance may be needed for males who have low serum T levels at a young age to monitor abnormal variations of T levels and ensure timely treatment when necessary to reduce PCa risk.
FLOURY ENDOSPERM16 encoding a NAD‐dependent cytosolic malate dehydrogenase plays an important role in starch synthesis and seed development in rice

Summary Starch is the most important form of energy storage in cereal crops. Many key enzymes involved in starch biosynthesis have been identified. However, the molecular mechanisms underlying the regulation of starch biosynthesis are largely unknown. In this study, we isolated a novel floury endosperm rice (Oryza sativa) mutant flo16 with defective starch grain (SG) formation. The amylose content and amylopectin structure were both altered in the flo16 mutant. Map‐based cloning and complementation tests demonstrated that FLO16 encodes a NAD‐dependent cytosolic malate dehydrogenase (CMDH). The ATP contents were decreased in the mutant, resulting in significant reductions in the activity of starch synthesis‐related enzymes. Our results indicated that FLO16 plays a critical role in redox homeostasis that is important for compound SG formation and subsequent starch biosynthesis in rice endosperm. Overexpression of FLO16 significantly improved grain weight, suggesting a possible application of FLO16 in rice breeding. These findings provide a novel insight into the regulation of starch synthesis and seed development in rice.
SECTION ONE: NUTRITIONAL ASPECTS OF SKELETAL DISEASES

Skeletal diseases may be induced by malnutrition that involves certain nutrients, notably calcium, phosphorus, and vitamin D, but also iodine, copper, zinc, manganese, fluorine, silicon, vitamin A and perhaps vitamin C, as well as protein and energy. The number of these nutrients and their interactions is so large that dietary intervention in bone abnormalities is likely to be most effective if directed at consumption of a diet that is completely balanced for growth, maturity, old age, or stress. Substitution of a good diet for a bad one is also likely to be more convenient and safer than most attempts at partial supplementation of the faulty diet in order to bring it into balance.
Transfer Adaptation Learning: A Decade Survey

The world we see is ever-changing and it always changes with people, things, and the environment. Domain is referred to as the state of the world at a certain moment. A research problem is characterized as transfer adaptation learning (TAL) when it needs knowledge correspondence between different moments/domains. TAL aims to build models that can perform tasks of target domain by learning knowledge from a semantic-related but distribution different source domain. It is an energetic research field of increasing influence and importance, which is presenting a blowout publication trend. This article surveys the advances of TAL methodologies in the past decade, and the technical challenges and essential problems of TAL have been observed and discussed with deep insights and new perspectives. Broader solutions of TAL being created by researchers are identified, i.e., instance reweighting adaptation, feature adaptation, classifier adaptation, deep network adaptation, and adversarial adaptation, which are beyond the early semisupervised and unsupervised split. The survey helps researchers rapidly but comprehensively understand and identify the research foundation, research status, theoretical limitations, future challenges, and understudied issues (universality, interpretability, and credibility) to be broken in the field toward generalizable representation in open-world scenarios.
Re-Thinking Untraceability in the CryptoNote-Style Blockchain

We develop new foundations on transaction untraceability for CryptoNote-style blockchain systems. In particular, we observe new attacks; develop theoretical foundations to model transaction untraceability; provide the least upper bound of transaction untraceability guarantee; provide ways to efficiently and automatically verify whether a given ledger achieves optimal transaction untraceability; and provide a general solution that achieves provably optimal transaction untraceability. Unlike previous cascade effect attacks (ESORICS' 17 and PETS' 18) on CryptoNote-style transaction untraceability, we consider not only a passive attacker but also an active adaptive attacker. Our observed attacks allow both types of attacker to trace blockchain transactions that cannot be traced by using the existing attacks. We develop a series of new games, which we call "The Sun-Tzu Survival Problem", to model CryptoNote-style blockchain transaction untraceability and our identified attacks. In addition, we obtain seven novel results, where three of them are negative and the rest are positive. In particular, thanks to our abstract game, we are able to build bipartite graphs to model transaction untraceability, and provide reductions to formally relate the hardness of calculating untraceability to the hardness of calculating the number of perfect matchings in all possible bipartite graphs. We prove that calculating transaction untraceability is a #P-complete problem, which is believed to be even more difficult to solve than NP problems. In addition, we provide the first result on the least upper bound of transaction untraceability. Moreover, through our theoretical results, we are able to provide ways to efficiently and automatically verify whether a given ledger achieves optimal transaction untraceability. Furthermore, we propose a simple strategy for CryptoNote-style blockchain systems to achieve optimal untraceability. We take Monero as a concrete example to demonstrate how to apply this strategy to optimise the untraceability guarantee provided by Monero.
Molecular Imaging of Vascular Calcification with 18F-Sodium-Fluoride in Patients Infected with Human Immunodeficiency Virus

18F-Sodium Fluoride (NaF) accumulates in areas of active hydroxyapatite deposition and potentially unstable atherosclerotic plaques. We assessed the presence of atherosclerotic plaques in 50 adult patients with HIV (HIV+) who had undergone two cardiac computed tomography scans to measure coronary artery calcium (CAC) progression. CAC and its progression are predictive of an unfavorable prognosis. Tracer uptake was quantified in six arterial territories: aortic arch, innominate carotid artery, right and left internal carotid arteries, left coronary (anterior descending and circumflex) and right coronary artery. Thirty-one patients showed CAC progression and 19 did not. At least one territory with high NaF uptake was observed in 150 (50%) of 300 arterial territories. High NaF uptake was detected more often in non-calcified than calcified areas (68% vs. 32%), and in patients without than in those with prior CAC progression (68% vs. 32%). There was no correlation between clinical and demographic variables and NaF uptake. In clinically stable HIV+ patients, half of the arterial territories showed a high NaF uptake, often in the absence of macroscopic calcification. NaF uptake at one time point did not correlate with prior progression of CAC. Prospective studies will demonstrate the prognostic significance of high NaF uptake in HIV+ patients.
Average-Case Completeness in Tag Systems

To prove average-case NP-completeness for a problem, we must choose a known average-case complete problem and reduce it to that problem. Unfortunately, the set of options to choose from is far smaller than for standard (worst-case) NP-completeness. In an effort to help remedy this we focus on tag systems, which due to their extreme simplicity have been a target for other types of reductions for many problems including the matrix mortality problem, the Post correspondence problem, the universality of cellular automaton Rule 110, and all of the smallest universal single-tape Turing machines. Here we show that a tag system can efficiently simulate a Turing machine even when the input is provided in an extremely simple encoding which adds just log n carefully set bits to encode an arbitrary Turing machine input of length n. As a result we show that the bounded halting problem for nondeterministic tag systems is average-case NP-complete. This result is unexpected when one considers that in the current state of the art for simple universal systems it had appeared that there was a trade-off whereby simpler systems required more complicated input encodings. In other words, although simple systems can compute interesting things, they had appeared to require very carefully encoded inputs in order to do so. Our result surprisingly goes in the opposite direction by giving the first average-case completeness result for such a simple model of computation. In ongoing work we have already found applications of our result having used it to give average-case NP-completeness results for a 2D generalization of the Collatz function, a nondeterministic version of the 2D elementary functions studied by Koiran and Moore, 3D piecewise affine maps, and bounded Post correspondence problem instances that use simpler word pairs than previous results.
Genome-Wide Copy Number Variation Association Study of Atrial Fibrillation Related Thromboembolic Stroke

Atrial fibrillation (AF) is a common cardiac arrhythmia and is one of the major causes of ischemic stroke. In addition to the clinical factors such as CHADS2 or CHADS2-VASC score, the impact of genetic factors on the risk of thromboembolic stroke in patients with AF has been largely unknown. Single-nucleotide polymorphisms in several genomic regions have been found to be associated with AF. However, these loci do not contribute to all the genetic risks of AF or AF related thromboembolic risks, suggesting that there are other genetic factors or variants not yet discovered. In the human genome, copy number variations (CNVs) could also contribute to disease susceptibility. In the present study, we sought to identify CNVs determining the AF-related thromboembolic risk. Using a genome-wide approach in 109 patients with AF and thromboembolic stroke and 14,666 controls from the Taiwanese general population (Taiwan Biobank), we first identified deletions in chromosomal regions 1p36.32-1p36.33, 5p15.33, 8q24.3 and 19p13.3 and amplifications in 14q11.2 that were significantly associated with AF-related stroke in the Taiwanese population. In these regions, 148 genes were involved, including several microRNAs and long non-recoding RNAs. Using a pathway analysis, we found deletions in GNB1, PRKCZ, and GNG7 genes related to the alpha-adrenergic receptor signaling pathway that play a major role in determining the risk of an AF-related stroke. In conclusion, CNVs may be genetic predictors of a risk of a thromboembolic stroke for patients with AF, possibly pointing to an impaired alpha-adrenergic signaling pathway in the mechanism of AF-related thromboembolism.
Population Substructure Has Implications in Validating Next-Generation Cancer Genomics Studies with TCGA

In the era of large genetic and genomic datasets, it has become crucially important to validate results of individual studies using data from publicly available sources, such as The Cancer Genome Atlas (TCGA). However, how generalizable are results from either an independent or a large public dataset to the remainder of the population? The study presented here aims to answer that question. Utilizing next generation sequencing data from endometrial and ovarian cancer patients from both the University of Iowa and TCGA, genomic admixture of each population was analyzed using STRUCTURE and ADMIXTURE software. In our independent data set, one subpopulation was identified, whereas in TCGA 4–6 subpopulations were identified. Data presented here demonstrate how different the genetic substructures of the TCGA and University of Iowa populations are. Validation of genomic studies between two different population samples must be aware of, account for and be corrected for background genetic substructure.
Host Selection Behavior of the Green Peach Aphid, Myzus persicae, in Response to Volatile Organic Compounds and Nitrogen Contents of Cabbage Cultivars

Plants emit volatile organic compounds (VOCs) in response to herbivore attack. VOCs emitted from the Chinese cabbage cultivars in response to the damage by the green peach aphid, Myzus persicae, were unknown. Using a solid-phase microextraction-based headspace collection method, we investigated and compared the emissions of VOCs from seven Chinese cabbage cultivars (Qibao, Qingan 80, Lvlong, Yuanbao, Qingan 70, Jinlv, and Lvqiu 66) in response to M. persicae attack. Our results showed that the VOCs emitted from the cultivars Qingan 80 and Yuanbao differed significantly from the other cultivars in response to the attraction of wingless M. persicae. Most importantly, out of the 27 detected compounds, α-caryophyllene was detected only in Qingan 80 and Qibao, but not in the other five cultivars. Among the compounds detected, 2 monoterpene and 12 terpenes were predominant in all cabbage cultivars. Furthermore, the wingless M. persicae showed preference to Qingan 80 while it had the highest nitrogen content among the tested cultivars. Moreover, we found a remarkable relationship among M. persicae attraction, plant nitrogen content, and total volatile emissions. Nitrogen content of the plants has a significant impact on volatile emission and preference behavior of M. persicae. Our results indicate that the wingless M. persicae were efficient in their interspecific host selection with an ability to distinguish plant cultivar differences by leaf nitrogen content. This study will be helpful in understanding aphid host selection, and sets a stage to further study the attractant-based integrated aphid management programs.
Single-source Library for Enabling Seamless Assignment of Data-parallel Task-DAGs to CPUs and GPUs in Heterogeneous Architectures

Currently, the majority of devices is heterogeneous and comprises at least a multi-core CPU and a GPU. Exploiting these modules requires programmers to a) assign parallel activities to the different hardware resources, and b) code each activity through target-specific approaches x(e.g., multi-core CPUs and GPUs). Current frameworks do not provide high-productivity while guaranteeing performance comparable to low-level ones. Also, they often lack the easy exploration of possible task assignments to the heterogeneous resources, mainly because the assignment needs to be done in advance and the targets have software incompatibilities. This paper introduces task-DAGs (Directed Acyclic Graph) concepts into PHAST, a single-source data-parallel library that supports multi-core CPUs and NVIDIA GPUs. The resulting framework allows postponing the task-to-target assignment to the testing or runtime phase. In fact, each task is coded in a target-agnostic fashion and can be automatically optimized for a specific platform. The consequent productivity effects are shown for a computer-vision benchmark comparing to a SYCL implementation and performing an automatic task assignment for maximum resources utilization.
3D printing approaches for cardiac tissue engineering and role of immune modulation in tissue regeneration

Conventional tissue engineering, cell therapy, and current medical approaches were shown to be successful in reducing mortality rate and complications caused by cardiovascular diseases (CVDs). But still they have many limitations to fully manage CVDs due to complex composition of native myocardium and microvascularization. Fabrication of fully functional construct to replace infarcted area or regeneration of progenitor cells is important to address CVDs burden. Three-dimensional (3D) printed scaffolds and 3D bioprinting technique have potential to develop fully functional heart construct that can integrate with native tissues rapidly. In this review, we presented an overview of 3D printed approaches for cardiac tissue engineering, and advances in 3D bioprinting of cardiac construct and models. We also discussed role of immune modulation to promote tissue regeneration.