Miracle-dz/UniFAR-FTUs huggingface dataset:
Mutational Spectrum of Smith-Lemli-Opitz Syndrome Patients in Hungary

Smith-Lemli-Opitz (SLO) syndrome is an autosomal recessive disorder characterized by multiple congenital abnormalities and mental retardation. The condition is caused by the deficiency of 7-dehydrocholesterol reductase (DHCR7) which catalyzes the final step in cholesterol biosynthesis. Biochemical diagnosis is based on increased concentration of 7-dehydrocholesterol (7-DHC) in the patient serum. Both life expectancy and quality of life are severely affected by the disease. The estimated prevalence of SLO syndrome ranges between 1:20,000 and 1:40,000 among Caucasians. Although the mutational spectrum of the disease is wide, approximately 10 mutations are responsible for more than 80% of the cases. These mutations show a large interethnic variability. There are no mutation distribution data from Hungary to date. Thirteen patients were diagnosed with SLO syndrome in our laboratory. As first-line tests, serum 7-DHC and total cholesterol were measured and, in positive cases, molecular genetic analysis of the DHCR7 gene was performed. Complete genetic background of the disease could be identified in 12 cases. In 1 case only 1 mutation was detected in a heterozygote form. One patient was homozygous for the common splice site mutation c.964–1G>C, while all other patients were compound heterozygotes. One novel missense mutation, c.374A>G (p.Tyr125Cys) was identified.
Masalah Kegagalan dan Kelewatan Pengagihan Harta Pusaka di Malaysia

Kelewatan serta kegagalan permohonan bagi menyelesaikan pembahagian harta pusaka bukanlah satu fenomena terpencil dalam masyarakat kita. Faktor yang menyumbang kepada permasalahan ini adalah berikutan daripada sikap pewaris serta proses pentadbiran harta pusaka di negara ini. Risiko kepada kegagalan penyelesaian harta pusaka yang dikemukakan ini sebenarnya boleh mengundang pelbagai implikasi buruk dari sudut undang-undang, ekonomi, agama dan sosial. Meneliti beberapa kesan negatif yang bakal dihadapi natijah daripada kegagalan dan kelewatan pembahagian harta pusaka selepas kematian, adalah perlu kepada masyarakat untuk mengatur perancangan awal bagi menguruskan harta. Walau bagaimanapun, hasil penelitian menunjukkan masyarakat di negara ini kurang mempunyai kecenderungan untuk membuat perancangan pengagihan harta secara teliti terutamanya dalam membuat perancangan awal. Kesan daripada itu, mereka telah bergantung sepenuhnya kepada sistem pewarisan harta selepas kematian iaitu pembahagian secara faraid. Oleh yang demikian, persepsi masyarakat yang berpandangan bahawa perancangan awal pengagihan harta tidak diperlukan sama sekali memandangkan harta boleh diagihkan melalui sistem faraid sewajarnya dikikis. Sebaliknya, perancangan pengagihan harta semasa hidup seperti pemberian melalui hibah dan wasiat perlu dipertingkatkan bagi mengelakkan masalah tersebut kerana ia jelas merugikan masyarakat Islam.
Meta‐Analysis of the Effects of Human Disturbance on Seed Dispersal by Animals

Animal‐mediated seed dispersal is important for sustaining biological diversity in forest ecosystems, particularly in the tropics. Forest fragmentation, hunting, and selective logging modify forests in myriad ways and their effects on animal‐mediated seed dispersal have been examined in many case studies. However, the overall effects of different types of human disturbance on animal‐mediated seed dispersal are still unknown. We identified 35 articles that provided 83 comparisons of animal‐mediated seed dispersal between disturbed and undisturbed forests; all comparisons except one were conducted in tropical or subtropical ecosystems. We assessed the effects of forest fragmentation, hunting, and selective logging on seed dispersal of fleshy‐fruited tree species. We carried out a meta‐analysis to test whether forest fragmentation, hunting, and selective logging affected 3 components of animal‐mediated seed dispersal: frugivore visitation rate, number of seeds removed, and distance of seed dispersal. Forest fragmentation, hunting, and selective logging did not affect visitation rate and were marginally associated with a reduction in seed‐dispersal distance. Hunting and selective logging, but not fragmentation, were associated with a large reduction in the number of seeds removed. Fewer seeds of large‐seeded than of small‐seeded tree species were removed in hunted or selectively logged forests. A plausible explanation for the consistently negative effects of hunting and selective logging on large‐seeded plant species is that large frugivores, as the predominant seed dispersers for large‐seeded plant species, are the first animals to be extirpated from hunted or logged forests. The reduction in forest area after fragmentation appeared to have weaker effects on frugivore communities and animal‐mediated seed dispersal than hunting and selective logging. The differential effects of hunting and selective logging on large‐ and small‐seeded tree species underpinned case studies that showed disrupted plant‐frugivore interactions could trigger a homogenization of seed traits in tree communities in hunted or logged tropical forests.
Product Bundling – The Effects of Quality Uncertainty and Complementarities on Individual Judgment and Choice

Product bundling of products is prevalent in markets for information goods on the Internet, computer hardware and software goods. Individuals’ judgment and choice of IT product bundles have crucial effects on consumer demand of bundles and market conduct by firms. However, factors affecting consumers’ judgment and choice of IT product bundles, and the resultant impacts have not been clearly documented in the IS literature. In particular, research in product bundling has not examined the effect of product quality uncertainty (in both the focal and supplement components) and the impact of including either complementary or non-complementary components in a bundle. We pose these research questions: 1) Do individuals’ judgment and choice of product bundles depend on whether the focal or supplement bundle item is complementary or non-complementary to each other? 2) Do individuals’ judgment and choice of product bundles depend on the presence of product quality uncertainty in either the focal or supplement bundle component? Drawing from various research streams, we formulate hypotheses to evaluate the answers to our research questions. To test these hypotheses, we conduct laboratory experiments to study individual judgments and choices of IT product bundles. Research on the aboveproposed issues has important implications for practice and research in IT product and brand extensions, and the bundling of digital information products.
Assessing Language Models with Scaling Properties

Language models have primarily been evaluated with perplexity. While perplexity quantifies the most comprehensible prediction performance, it does not provide qualitative information on the success or failure of models. Another approach for evaluating language models is thus proposed, using the scaling properties of natural language. Five such tests are considered, with the first two accounting for the vocabulary population and the other three for the long memory of natural language. The following models were evaluated with these tests: n-grams, probabilistic context-free grammar (PCFG), Simon and Pitman-Yor (PY) processes, hierarchical PY, and neural language models. Only the neural language models exhibit the long memory properties of natural language, but to a limited degree. The effectiveness of every test of these models is also discussed.
Specification and construction of performability models

Model-based performability evaluation of computer and communication systems requires accurate and e cient techniques for model construction as well as model solution. Moreover, as the physical and logical complexity of such systems continues to grow, there is need for increased care in specifying just what is to be constructed in response to the aims of a given evaluation study. This presentation thus focuses on speci cation and construction aspects of performabilitymodeling, under the assumption that construction (and subsequent solution) are automated. Concepts and methods are described for each, with emphasis on specifying/realizing the relation between a base stochastic model and the measures it must support. Although stochastic activity networks are chosen as the vehicle for base model speci cation, many of the techniques employed convey principles that apply as well to other speci cation constructs.
Procalcitonin guidance in patients with lower respiratory tract infections: a systematic review and meta-analysis

Abstract Although effective for bacterial lower respiratory tract infections (LRTIs), antibiotic treatment is often incorrectly prescribed for non-bacterial LRTIs. Procalcitonin has emerged as a promising biomarker to diagnose bacterial infections and guide antibiotic treatment decisions. As part of a regulatory submission to the U.S. Food and Drug Administration, this systematic review and meta-analysis summarizes the effects of procalcitonin-guided antibiotic stewardship on antibiotic use and clinical outcomes in adult LRTI patients. PubMed and the Cochrane Database of Systematic Reviews were searched for English-language randomized controlled trials published between January 2004 and May 2016. Random and fixed effects meta-analyses were performed to study efficacy (initiation of antibiotics, antibiotic use) and safety (mortality, length of hospital stay). Eleven trials were retained, comprising 4090 patients. Procalcitonin-guided patients had lower odds of antibiotic initiation (odds ratio: 0.26; 95% confidence interval [CI]: 0.13–0.52) and shorter mean antibiotic use (weighted mean difference: −2.15 days; 95% CI: −3.30 to −0.99) compared to patients treated with standard care. Procalcitonin use had no adverse impact on mortality (relative risk: 0.94; 95% CI: 0.69–1.28) and length of hospital stay (weighted mean difference: −0.15 days; 95% CI: −0.60 to 0.30). Procalcitonin guidance reduces antibiotic initiation and use among adults with LRTIs with no apparent adverse impact on length of hospital stay or mortality.
MR Tractography for preoperative planning in patients with cerebral tumors in eloquent areas

Resection of the maximum amount of tumoral tissue while preserving the function of the brain within or neighboring the tumor region established itself as a fundamental goal of modern oncologic neurosurgery. A major step in preoperative mapping of eloquent cerebral cortex was taken reliably through the use of functional magnetic resonance imaging. However it does not provide any information about the white matter tracts that may be affected by invasive, intrinsic brain tumors. The advances in diffusion-tensor (DT) imaging techniques have been used to map white matter tracts in the normal brain. The aim of this study was to demonstrate the role of DT imaging in preoperative mapping of white matter tracts in relation to cerebral neoplasms and the way it can influence the operative decision in our practice. Ten patients with brain malignancies within or neighboring eloquent cortical areas (nine glioblastoma and one grade two astrocytoma) underwent DT imaging examinations prior to tumor excision. Anatomical information about white matter tract location, orientation, and projections was obtained in every patient. Depending on the tumor type and location, evidence of white matter tract edema (one patient), infiltration (one patient), displacement (five patients), and disruption (three patients) could be assessed with the aid of DT imaging in each case. Diffusion-tensor imaging allowed for visualization of white matter tracts and was found to be beneficial in the surgical planning for patients with intrinsic brain tumors. The authors’ experience with DT imaging indicates that anatomically intact fibers may be present in abnormal-appearing areas of the brain. Whether resection of these involved fibers results in subtle postoperative neurological deficits requires further systematic study.
Identification of potential hazardous events for an Unmanned Protective Vehicle

The project Automated Unmanned Protective Vehicle for Highway Hard Shoulder Road Works (aFAS) aims to develop an unmanned protective vehicle to reduce the risk of injuries due to crashes for road workers. To ensure functional safety during operation in public traffic the system shall be developed following the ISO 26262 standard. After defining the functional range in the item definition, a hazard analysis and risk assessment has to be done. The ISO 26262 standard gives hints how to process this step and demands a systematic way to identify system hazards. Best practice standards provide systematic ways for hazard identification, but lack applicability for automated vehicles due to the high variety and number of different driving situations even with a reduced functional range. This contribution proposes a new method to identify hazardous events for a system with a given functional description. The method utilizes a skill graph as a functional model of the system and an overall definition of a scene for automated vehicles to identify potential hazardous events. An adapted Hazard and Operability Analysis approach is used to identify system malfunctions. A combination of all methods results in operating scenes with potential hazardous events. These can be assessed afterwards towards their criticality. A use case example is taken from the current development phase of the project aFAS.
Chemerin in a Mouse Model of Non-alcoholic Steatohepatitis and Hepatocarcinogenesis.

BACKGROUND/AIM Non-alcoholic steatohepatitis (NASH) is a risk factor for hepatocellular carcinoma (HCC). The adipokine chemerin protects from HCC and is reduced in human HCC. In this study, chemerin expression was analyzed in a murine model of NASH-HCC. MATERIALS AND METHODS Serum and hepatic chemerin, and ex vivo chemerin receptor activation were monitored in NASH and NASH-HCC in mice fed a low-methionine diet deficient in choline after initiation of tumors by injection of diethylnitrosamine. RESULTS In non-tumorous liver tissues, the extent of hepatic steatosis, and the levels of proteins regulating hepatic lipids and liver fibrosis were similar in NASH and NASH-associated HCC. Systemic and hepatic chemerin, and chemerin receptor activation were not changed in HCC. Liver tumors only developed in diethylnitrosamine-injected mice and their number was increased in NASH. Chemerin protein was induced in liver in NASH, but was unchanged in HCC tissues. CONCLUSION Hepatic and serum chemerin and ex vivo analyzed chemerin receptor activation do not differ in murine NASH-associated HCC when compared to NASH. Hepatic tumors still develop despite high endogenous levels of serum and liver chemerin protein.
What’s in a Face? How Face Gender and Current Affect Influence Perceived Emotion

Faces drive our social interactions. A vast literature suggests an interaction between gender and emotional face perception, with studies using different methodologies demonstrating that the gender of a face can affect how emotions are processed. However, how different is our perception of affective male and female faces? Furthermore, how does our current affective state when viewing faces influence our perceptual biases? We presented participants with a series of faces morphed along an emotional continuum from happy to angry. Participants judged each face morph as either happy or angry. We determined each participant’s unique emotional ‘neutral’ point, defined as the face morph judged to be perceived equally happy and angry, separately for male and female faces. We also assessed how current state affect influenced these perceptual neutral points. Our results indicate that, for both male and female participants, the emotional neutral point for male faces is perceptually biased to be happier than for female faces. This bias suggests that more happiness is required to perceive a male face as emotionally neutral, i.e., we are biased to perceive a male face as more negative. Interestingly, we also find that perceptual biases in perceiving female faces are correlated with current mood, such that positive state affect correlates with perceiving female faces as happier, while we find no significant correlation between negative state affect and the perception of facial emotion. Furthermore, we find reaction time biases, with slower responses for angry male faces compared to angry female faces.
A Tight Approximation for Submodular Maximization with Mixed Packing and Covering Constraints

Motivated by applications in machine learning, such as subset selection and data summarization, we consider the problem of maximizing a monotone submodular function subject to mixed packing and covering constraints. We present a tight approximation algorithm that for any constant $\epsilon >0$ achieves a guarantee of $1-\frac{1}{\mathrm{e}}-\epsilon$ while violating only the covering constraints by a multiplicative factor of $1-\epsilon$. Our algorithm is based on a novel enumeration method, which unlike previous known enumeration techniques, can handle both packing and covering constraints. We extend the above main result by additionally handling a matroid independence constraints as well as finding (approximate) pareto set optimal solutions when multiple submodular objectives are present. Finally, we propose a novel and purely combinatorial dynamic programming approach that can be applied to several special cases of the problem yielding not only {\em deterministic} but also considerably faster algorithms. For example, for the well studied special case of only packing constraints (Kulik {\em et. al.} [Math. Oper. Res. `13] and Chekuri {\em et. al.} [FOCS `10]), we are able to present the first deterministic non-trivial approximation algorithm. We believe our new combinatorial approach might be of independent interest.
Antenna pattern retrieval from measurements in non-ideal anechoic chamber

The study focuses on the measurement procedure and the algorithm for retrieval of the true radiation pattern of the antenna from data measured in non-ideal environments, which are insufficient distance from the source antenna and scattering from the walls of the chamber. Unlike the previous works, a concept of converging cluster of plane waves used not only to approximate the primary illuminating field, but also to account for waves reflected from the measuring chamber walls. In addition, expansion in the number of basis functions instead of a set of points represents the sought-for antenna pattern. This leads to bettering the reconstruction algorithm stability. The results of modeling various tasks illustrate how interesting can be relief of fields brought forth by clusters of waves inside and outside the test zone.
Fair Division Under Cardinality Constraints

We consider the problem of fairly allocating indivisible goods, among agents, under cardinality constraints and additive valuations. In this setting, we are given a partition of the entire set of goods---i.e., the goods are categorized---and a limit is specified on the number of goods that can be allocated from each category to any agent. The objective here is to find a fair allocation in which the subset of goods assigned to any agent satisfies the given cardinality constraints. This problem naturally captures a number of resource-allocation applications, and is a generalization of the well-studied unconstrained fair division problem. The two central notions of fairness, in the context of fair division of indivisible goods, are envy freeness up to one good (EF1) and the (approximate) maximin share guarantee (MMS). We show that the existence and algorithmic guarantees established for these solution concepts in the unconstrained setting can essentially be achieved under cardinality constraints. Furthermore, focusing on the case wherein all the agents have the same additive valuation, we establish that EF1 allocations exist even under matroid constraints.
Optimal-Margin Evolutionary Classifier

We introduce a novel approach for discriminative classification using evolutionary algorithms. We first propose an algorithm to optimize the total loss value using a modified 0–1 loss function in a 1-D space for classification. We then extend this algorithm for multidimensional classification using an evolutionary algorithm. The proposed evolutionary algorithm aims to find a hyperplane that best classifies instances while minimizing the classification risk. We test particle swarm optimization, evolutionary strategy (ES), and covariance matrix adaptation ES for optimization purposes. After parameter selection, we compare our results with well-established and state-of-the-art classification algorithms, for both binary and multiclass classification, on 23 benchmark classification problems, with and without noise and outliers. We also compare these methods on a seizure detection task for 12 epileptic patients. Results show that the performance of the proposed algorithm is significantly (Wilcoxon test) better than all other methods in almost all problems tested. We also show that the proposed algorithm is significantly more robust against noise and outliers comparing to other methods. The running time of the algorithm is within a reasonable range for the solution of real-world classification problems.
Learning Cross-Modal Deep Embeddings for Multi-Object Image Retrieval using Text and Sketch

In this work we introduce a cross modal image retrieval system that allows both text and sketch as input modalities for the query. A cross-modal deep network architecture is formulated to jointly model the sketch and text input modalities as well as the the image output modality, learning a common embedding between text and images and between sketches and images. In addition, an attention model is used to selectively focus the attention on the different objects of the image, allowing for retrieval with multiple objects in the query. Experiments show that the proposed method performs the best in both single and multiple object image retrieval in standard datasets.
Social Interaction Contexts Bias the Perceived Expressions of Interactants

The present study sought to determine whether contextual information available when viewing social interactions from third-person perspectives may influence observers’ perception of the interactants’ facial emotion. Observers judged whether the expression of a target face was happy or fearful, in the presence of a happy, aggressive, or neutral interactant. In 2 experiments, the same target expressions were judged to be happier when presented in the context of a happy interactant than when interacting with a neutral or aggressive partner. We failed to show that the target expression was judged as more fearful when interacting with an aggressive partner. Importantly, observers’ perception of the target expression was not modulated by the emotion of the context interactant when the interactants were presented back-to-back, suggesting that the bias depends on the presence of an intact interaction arrangement. These results provide valuable insight into how social contextual effects shape our perception of facial emotion.