Miracle-dz/UniFAR-FTUs huggingface dataset:
Use of multiplex ligation‐dependent probe amplification increases the detection rate for 11p15 epigenetic alterations in Silver–Russell syndrome

Silver–Russell syndrome (SRS) describes a malformation syndrome with severe intrauterine and postnatal growth retardation. Currently, two major (epi)mutations have been described: while approximately 10% of patients carry a maternal uniparental disomy of chromosome 7 (UPD7), 35–60% show a hypomethylation at the H19 differentially methylated regions (DMRs) in 11p15. Until recently, a Southern‐blot based test was routinely used to identify epimutation carriers. Nevertheless, this test was time consuming and hampered by the huge amount of genomic DNA needed. With the methylation‐specific multiplex ligation‐dependent probe amplification assay (MLPA) for SRS, a PCR‐based test is now available, allowing the analysis also of small amounts of DNA. Probes in this assay hybridize to the H19 DMRs but do not cover the genomic target of the Southern‐blot probe. We now screened 72 patients with SRS by MLPA. Hypomethylation of the H19 DMRs was confirmed in all patients analyzed by Southern blot. In addition, we identified six individuals with hypomethylation of the H19 DMR who had previously normal blot results. This discrepancy can be explained by the observed generally lower degree of demethylation in this group, possibly not detectable by the less sensitive Southern‐blot method but also with a varying degree of methylation at different DMRs in the same individual. Apart from hypomethylation in the H19 DMR, we observed a slight demethylation for one of the IGF2 probes. The total detection rate of 11p15 hypomethylation is now increased to >38%. Considering maternal UPD7 and chromosomal aberrations, (epi)genetic alterations now account for more than 50% of SRS patients. In summary, MLPA represents an easy, low cost and reliable system in the molecular diagnostics of SRS.
PENGARUH SOCIAL MEDIA MARKETING TERHADAP BRAND TRUST PADA FOLLOWERS INSTAGRAM DOMPET DHUAFA CABANG YOGYAKARTA

Penelitian ini berlatar belakang social media marketing, sebuah teknik pemasaran menggunakan media sosial yang baru berkembang pesat saat ini. Banyak perusahaan yang telah menggunakannya termasuk lembaga nirlaba seperti Dompet Dhuafa Cabang Yogyakarta. Dengan tersedianya jaringan yang terhubung diseluruh penjuru dunia. Teknik ini bisa dimanfaatkan untuk membuktikan bukti sosial lembaga tersebut untuk membangun brand trust. Penelitian ini bertujuan untuk mengetahui pengaruh social media marketing terhadap terhadap brand trust pada followers Instagram Dompet Dhuafa Cabang Yogyakarta. Dalam penelitian ini, peneliti menggunakan metode penelitian kuantitatif dengan melakukan survei online kepada followers akun Instagram Dompet Dhuafa Cabang Yogyakarta yang berjumlah 100 sampel. Metode yang digunakan dalam pengambilan sampel yaitu probability sampling dengan teknik simple random sampling. Teknik analisis yang digunakan dalam penelitian ini adalah uji validitas, uji reliabilitas, analisis deskriptif kuantitatif, uji asumsi (uji normalitas, uji linieritas, dan uji heteroskedastisitas), dan regresi linier sederhana dengan uji hipotesis (uji t dan uji koefisien determinasi). Hasil penelitian menunjukkan bahwa social media marketing berpengaruh positif dan signifikan terhadap brand trust. Dengan melihat nilai beta pada kolom unstandardized coefficients adalah 0,398 dan uji t diketahui nilai t hitung adalah 10,835 lebih besar dari t tabel dengan nilai 1,658. Nilai R square adalah 0,545, berarti bahwa sebesar 54,5% brand trust yang terjadi dapat dijelaskan dengan variabel social media marketing.
Visualizing similarity between program executions

Multidimensional scaling (MDS) is a technique for visualizing multidimensional data points as a 2D scatter plot. It can be applied to execution profiles of software to reveal how similar executions are to one another. This is useful for certain software engineering applications, which require accurate representation of small dissimilarities and nearest neighbor relationships. However, the high-dimensionality of profiles can cause MDS techniques to represent small dissimilarities poorly. We evaluate several variants of MDS on large sets of profiles, to see which techniques produce the most accurate displays. These include four previously proposed techniques -classical scaling followed by iterative majorization, energy minimization, ordinal AIDS, and cluster differences scaling - and two techniques of our invention - hierarchical MDS and sparse region scaling. The results suggest that each technique except ordinal MDS can significantly improve the representation of small dissimilarities between program executions and that hierarchical MDS and sparse region scaling perform best overall
Both ciliary and non-ciliary functions of Foxj1a confer Wnt/β-catenin signaling in zebrafish left-right patterning

ABSTRACT The Wnt/β-catenin pathway is implicated in left-right (LR) axis determination; however, the underlying mechanism remains elusive. Prompted by our recent discovery that Wnt signaling regulates ciliogenesis in the zebrafish Kupffer's vesicle (KV) via Foxj1a, a ciliogenic transcription factor, we decided to elucidate functions of Foxj1a in Wnt-regulated LR pattern formation. We showed that targeted injection of wnt8a mRNA into a single cell at the 128-cell stage is sufficient to induce ectopic foxj1a expression and ectopic cilia. By interrogating the transcription circuit of foxj1a regulation, we found that both Lef1 and Tcf7 bind to a consensus element in the foxj1a promoter region. Depletion of Lef1 and Tcf7 inhibits foxj1a transcription in the dorsal forerunner cells, downregulates cilia length and number in KV, and randomizes LR asymmetry. Targeted overexpression of a constitutively active form of Lef1 also induced an ectopic protrusion that contains ectopic transcripts for sox17, foxj1a, and charon, and ectopic monocilia. Further genetic studies using this ectopic expression platform revealed two distinct functions of Foxj1a; mediating Wnt-governed monocilia length elongation as well as charon transcription. The novel Foxj1a-charon regulation is conserved in KV, and importantly, it is independent of the canonical role of Foxj1a in the biosynthesis of motile cilia. Together with the known function of motile cilia movement in generating asymmetric expression of charon, our data put forward a hypothesis that Foxj1a confers both ciliary and non-ciliary functions of Wnt signaling, which converge on charon to regulate LR pattern formation. Summary: Using a targeted overexpression platform, we showed that Wnt activation induces ectopic foxj1a expression and ectopic cilia formation, and revealed two distinct roles of Foxj1a in conferring Wnt-governed left-right patterning.
$Z$-Axis Magnetometers for MEMS Inertial Measurement Units Using an Industrial Process

The combination of multiaxis and multiparameter microelectromechanical systems (MEMS) in the same technology would result in very cheap and smart inertial measurement units (IMUs). In this paper, a <formula formulatype="inline"><tex Notation="TeX">$Z$</tex></formula>-axis Lorentz-force-based magnetometer whose design and optimization are reviewed taking into account the constraints of an industrial MEMS technology (process and packaging) already used for accelerometers and gyroscopes is presented. How this impacts the design guidelines is shown; in particular, a very compact device that can fit in the same package of the gyroscope to realize an all-MEMS seven-degree-of-freedom IMU is proposed and experimentally tested. The device shows a mechanical sensitivity of around 0.8 <formula formulatype="inline"><tex Notation="TeX">$\hbox{aF}/(\mu\hbox{T} \cdot \hbox{mA})$</tex></formula> with a resolution of 520 <formula formulatype="inline"><tex Notation="TeX">$(\hbox{nT} \cdot \hbox{mA})/\sqrt{\hbox{Hz}}$</tex></formula> over a signal bandwidth of 50 Hz at room temperature. Coupled to a transimpedance amplifier, the system shows an overall sensitivity of 150 <formula formulatype="inline"><tex Notation="TeX">$\mu\hbox{V}/\mu\hbox{T}$</tex></formula> at 250 <formula formulatype="inline"><tex Notation="TeX">$\mu\hbox{A}$</tex></formula> of peak driving current.
Compact Deep Convolutional Neural Networks for Image Classification

Convolutional Neural Network is efficient in learning hierarchical features from large datasets, but its model complexity and large memory foot prints are preventing it from being deployed to devices without a server backend support. Modern CNNs are always trained on GPUs or even GPU clusters with high speed computation power due to the immense size of the network. Methods on regulating the size of the network, on the other hand, are rarely studied. In this paper we present a novel compact architecture that minimizes the number of lower level kernels in a CNN by separating the color information from the original image. A 9-patch histogram extractor is built to exploit the separated color information. A higher level classifier learns the combined features from the compact CNN, trained only on grayscale image with limited number of kernels, and the histogram extractor. We apply our compact architecture to CIFAR-10 and Samsung Mobile Image Dataset. The proposed architecture has a recognition accuracy on par with those of state of the art CNNs, with 40% less parameters.
A comparison of i-gel™ and LMA Supreme™ in anesthetized and paralyzed children

Background Both the i-gel™ (i-gel) and LMA Supreme™ (Supreme) are new single-use second generation supraglottic airway devices available in pediatric sizes. This study was designed to investigate the i-gel in comparison with the Supreme in children undergoing general anesthesia. Methods One hundred children with American Society of Anesthesiologists physical status I or II undergoing general anesthesia were randomly assigned to either the i-gel or the Supreme group (50 children in each group). The device size was chosen according to weight of the children. We assessed the insertion success rate, insertion time, oropharyngeal leak pressure, grade of the fiberoptic glottic view, number of airway manipulations required, and postoperative complications. Results There were no differences in the demographic data between the two groups. The success rate of insertion was same in both groups. The insertion time of the i-gel was longer than that of Supreme (P = 0.004). The oropharyngeal leak pressure in the i-gel group was higher than that in the Supreme group (P = 0.013). On fiberoptic examination, the vocal cords were visible in 90% of the children in the i-gel group and in 96% of the children in the Supreme group. The number of airway manipulations required was higher in the i-gel group (14 cases) than in the Supreme group (1 case) (P < 0.001). There were no differences in complications including blood staining of the device and sore throat between both groups. Conclusions Both the i-gel and Supreme provided a satisfactory airway during general anesthesia in children. Compared to the Supreme, the i-gel demonstrated a higher oropharyngeal leak pressure, longer time for insertion, and a greater number of airway manipulations during anesthesia.
Hierarchical Mutual Nearest Neighbour Image Segmentation

This paper presents a hierarchical image segmentation algorithm based on the principle of mutual nearest neighbours. Image segmentation remains a great challenge in the computer vision community. To solve this problem, various algorithms have been proposed in the literature. However, most of these algorithms depend heavily on thresholds or parameter settings. Furthermore, the majority of them do not recognise the hierarchical nature of the problem. In particular, there might not be a single best segmentation for an image as the level of detail that should be present in a segmentation will depend on the purpose for which that segmentation will be used. Many algorithms might provide good results for a specific application, or in detecting a certain level of detail in an image, but may fail when they are applied to different types of images at a different level of detail. The method proposed in this paper generates a hierarchy of segmentations that retain different levels of detail. Thus, depending on the application, the segmentation that provides the required level of detail can be selected. Utilisation of only one meta-parameter in the process makes it applicable to any dataset as is. It can also be easily generalised to segment different types of images including 3D and multispectral images. Evaluation on the Berkeley BSD500 dataset and comparison with existing hierarchical segmentation algorithms provide superior results.
Receptor activator of NF-kappaB ligand (RANKL) and CD 31 expressions in chronic periodontitis patients before and after surgery

Aim of the study The present study investigated the hypothesis that upregulation of receptor activator of NF-kappaB ligand (RANKL) expression may be associated with upregulation of endothelial cell activitiy, which is common for periods of periodontal bone loss in chronic periodontitis. Material and methods RANKL expression of activated cells in soft tissue biopsies with CD 31 activity and the presence of RANKL and osteoprotegerin (OPG) in gingival crevicular fluid (GCF) were assessed in chronic periodontitis patients. Biopsies from 17 patients and 10 healthy subjects were immunohistochemically analyzed. Clinical measurements [plaque index (PI), the gingival index (GI), probing pocket depth (PPD), clinical attachment level (CAL) and gingival bleeding index (GBI)] and GCF samples were obtained before and after periodontal therapy. Results CD31 staining did not support the assumption that endothelium-like cells were predominantly associated with RANKL expression. Conclusions RANKL-positive cells were widely distributed in periodontitis patients giving only partial support to the hypothesis that RANKL expression is restricted to T- and B-cell activation.
Predictors Of Parental Discipline In Families Raising Youth With Hearing And Communication Disorders

Children with disabilities are at high risk for several forms of maltreatment, including abuse and neglect (Ammerman, Hersen, Van Hasselt, Lubetsky, & Sieck, 1994; Sullivan & Knutson, 1998b), and children with hearing and communication disorders comprise a substantial portion of children at risk (e.g., Sullivan & Knutson, 2000). For example, some literature investigating the parenting practices of parents raising children and adolescents with hearing and communication disorders suggests that these parents have a tendency to use physically harsh discipline practices (Knutson, Johnson, & Sullivan, 2004; Sullivan & Knutson, 1998b). Further, high prevalence rates of emotional and behavioral problems are documented in these youth (e.g., Greenberg & Kusché, 1989; Hindley, 1997; Prizant, Audet, Burke, & Hummel, 1990). Despite these findings, a limited amount of research focuses on understanding factors related to these undesired outcomes. Therefore, this study investigates the relationships among dimensions of parents’ psychological functioning and parent-child interactive processes in a culturally diverse, national sample of families raising children and adolescents with hearing and communication disorders. Results suggest that parents’ stress, depression, and anxiety as well as parent-child communication and involvement are important correlates of discipline practices and subsequent child behavior in families raising children and adolescents with hearing and communication disorders. Additionally, psychological aggression and parents’ depression are highly predictive factors in the use of corporal punishment. Also, psychological aggression and parenting stress are highly predictive of reported youth behavior problems. The information gained from this investigation may provide direction for assessment and therapeutic intervention with parents of children and adolescents who have hearing and communication disorders.
Optimal allocation of virtual machines for cloud-based multimedia applications

With the emergence of cloud computing, cloud-based multimedia applications have been increasingly adopted in recent years. There are two major challenges for multimedia application providers: the round trip time (RTT) requirement and the resource cost. In this paper, we study the virtual machine (VM) allocation problem for multimedia application providers to minimize the resource cost under RTT requirements. Specifically, we propose the optimal VM allocation schemes for single-site cloud and multi-site cloud, respectively. Moreover, we propose the greedy algorithms to efficiently allocate VMs in each case. Simulation results demonstrate that the proposed optimal VM allocation schemes can optimally allocate VMs to achieve a minimal resource cost.
Perceptions of Subjective Economic Well-Being and Support for Market Reform among China's Urban Population

This article examines whether subjective economic assessments have any impact on support for further market reforms among China's urban population, utilising a large survey of 10,716 people across 32 cities. The effect of subjective economic well-being on support for market reforms is an important issue for the Chinese government as it seeks to sell the benefits of increased globalisation and marketisation to its citizens. Our main finding is that people's assessment of the overall economic situation helps to explain support for market reform, although the relationship is weak, while people's assessment of their own economic circumstances does not influence support for reform. The findings are compared with those of similar studies for Central and Eastern Europe.
Automatic analysis of malware behavior using machine learning

Malicious software - so called malware - poses a major threat to the security of computer systems. The amount and diversity of its variants render classic security defenses ineffective, such that millions of hosts in the Internet are infected with malware in the form of computer viruses, Internet worms and Trojan horses. While obfuscation and polymorphism employed by malware largely impede detection at file level, the dynamic analysis of malware binaries during run-time provides an instrument for characterizing and defending against the threat of malicious software. In this article, we propose a framework for the automatic analysis of malware behavior using machine learning. The framework allows for automatically identifying novel classes of malware with similar behavior (clustering) and assigning unknown malware to these discovered classes (classification). Based on both, clustering and classification, we propose an incremental approach for behavior-based analysis, capable of processing the behavior of thousands of malware binaries on a daily basis. The incremental analysis significantly reduces the run-time overhead of current analysis methods, while providing accurate discovery and discrimination of novel malware variants.
Acoustic Resonance in a Model Ducted-Jet System

Jet engines are tested in so-called test cells, in which the desired environmental conditions are controlled. The jet plume is exhausted out of the test cell, usually through a diffuser. Under certain testing conditions, high-intensity pressure fluctuations (170 dB) can arise in such facilities. Their frequency is close to that of an acoustic normal mode of the exhaust-diffuser, but the mechanisms driving the resonance are unclear. In the present work the resonance phenomenon is studied using numerical simulations of a model configuration, which shares the key features of actual facilities: an underexpanded supersonic jet, a finite-length solid-wall shroud surrounding the jet, and the receptivity of acoustic disturbances to excite jet instabilities at the nozzle. For this configuration a high-amplitude resonance, qualitatively similar to that of experiments in actual facilities, is observed for a symmetric overexpanded M jet = 1.2 jet. This strongly resonant case is contrasted with a nonresonant ducted M jet = 1.5 jet in the same geometry, as well as with a free jet at M jet = 1.2. The hydrodynamic mechanism of this resonance is studied using linear stability analysis. The presence of excited acoustic modes of the duct is revealed by the Fourier analysis of the data. A numerical experiment shows that slight artificial damping of just the most excited acoustic mode suppresses the resonance.
Identification and Profiling of MicroRNAs from Skeletal Muscle of the Common Carp

The common carp is one of the most important cultivated species in the world of freshwater aquaculture. The cultivation of this species is particularly productive due to its high skeletal muscle mass; however, the molecular mechanisms of skeletal muscle development in the common carp remain unknown. It has been shown that a class of non-coding ∼22 nucleotide RNAs called microRNAs (miRNAs) play important roles in vertebrate development. They regulate gene expression through sequence-specific interactions with the 3′ untranslated regions (UTRs) of target mRNAs and thereby cause translational repression or mRNA destabilization. Intriguingly, the role of miRNAs in the skeletal muscle development of the common carp remains unknown. In this study, a small-RNA cDNA library was constructed from the skeletal muscle of the common carp, and Solexa sequencing technology was used to perform high throughput sequencing of the library. Subsequent bioinformatics analysis identified 188 conserved miRNAs and 7 novel miRNAs in the carp skeletal muscle. The miRNA expression profiling showed that, miR-1, miR-133a-3p, and miR-206 were specifically expressed in muscle-containing organs, and that miR-1, miR-21, miR-26a, miR-27a, miR-133a-3p, miR-206, miR-214 and miR-222 were differentially expressed in the process of skeletal muscle development of the common carp. This study provides a first identification and profiling of miRNAs related to the muscle biology of the common carp. Their identification could provide clues leading towards a better understanding of the molecular mechanisms of carp skeletal muscle development.
Personality Traits and Body Mass Index in a Korean Population

Background Overweight and obesity is a serious problem worldwide related to cardiovascular and other diseases. Personality traits are associated with the abnormal body mass indices (BMIs) indicative of overweight and obesity. However, the links between personality traits and BMI have been little studied in Korea. Methods We evaluated the association between personality traits and BMI in men and women using the rural Ansung and urban Ansan cohort from the Korean Genome Epidemiology Study, and the Kangbuk Samsung Hospital Cohort Study datasets. A shorter version of the original Revised Neuroticism-Extroversion-Openness Personality Inventory (NEO-PI-R) was used to measure the five-factor model of personality (neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness). Results Data from a total of 1,495 men (mean age 60.0±9.8 years; mean BMI 24.3±3.0 kg/m2) and 2,547 women (mean age 47.0±15.5 years; mean BMI 22.8±3.4 kg/m2) were included in the analysis. Compared with the normal weight groups, overweight and obese men scored higher on openness to experience and lower on conscientiousness. Overweight and obese women scored lower on neuroticism and openness to experience and higher on agreeableness. Extraversion was positively associated with BMI in men (β = 0.032, P<0.05). BMI and waist circumference were significantly increased in individuals who were less dutiful. In women, neuroticism was inversely associated with BMI (β = −0.026, P<0.05). Openness to experience was negatively, and agreeableness was positively, associated with BMI (openness to experience: β = −0.072, agreeableness β = 0.068) and waist circumference (openness to experience: β = −0.202, agreeableness: β = 0.227) (P<0.05). Conclusion Personality traits were associated with underweight, overweight, and obesity in men and women. Increased understanding of the underlying factors contributing to this association will aid in the prevention and treatment of abnormal BMI.