Miracle-dz/UniFAR-FTUs huggingface dataset:
A genetic basis for cancer sex differences revealed in Xp11 translocation renal cell carcinoma

Xp11 translocation renal cell carcinoma (tRCC) is a female-predominant kidney cancer driven by translocations between the TFE3 gene on chromosome Xp11.2 and partner genes located on either chrX or on autosomes. The rearrangement processes that underlie TFE3 fusions, and whether they are linked to the female sex bias of this cancer, are largely unexplored. Moreover, whether oncogenic TFE3 fusions arise from both the active and inactive X chromosomes in females remains unknown. Here we address these questions by haplotype-specific analyses of whole-genome sequences of 29 tRCC samples from 15 patients and by re-analysis of 145 published tRCC whole-exome sequences. We show that TFE3 fusions universally arise as reciprocal translocations with minimal DNA loss or insertion at paired break ends. Strikingly, we observe a near exact 2:1 female:male ratio in TFE3 fusions arising via X:autosomal translocation (but not via X inversion), which accounts for the female predominance of tRCC. This 2:1 ratio is at least partially attributable to oncogenic fusions involving the inactive X chromosome and is accompanied by partial re-activation of silenced chrX genes on the rearranged chromosome. Our results highlight how somatic alterations involving the X chromosome place unique constraints on tumor initiation and exemplify how genetic rearrangements of the sex chromosomes can underlie cancer sex differences.
CRISPR-DIPOFF: an interpretable deep learning approach for CRISPR Cas-9 off-target prediction

CRISPR Cas-9 is a groundbreaking gene-editing tool that harnesses bacterial defense systems to alter DNA sequences accurately. This innovative technology holds vast promise in multiple domains like biotechnology, agriculture, and medicine. However, such power does not come without its own peril, and one such issue is the potential for unintended modifications (Off-Target), which highlights the need for accurate prediction and mitigation strategies. Though previous studies have demonstrated improvement in Off-Target prediction capability with the application of deep learning, they often struggle with the precision-recall trade-off, limiting their effectiveness and do not provide proper interpretation of the complex decision-making process of their models. To address these limitations, we have thoroughly explored deep learning networks, particularly the recurrent neural network (RNN) and transformer based models, leveraging their established success in handling sequence data. Furthermore, we have employed genetic algorithm for hyperparameter tuning to optimize these models’ performance. The results from our experiments demonstrate significant performance improvement compared to the current state-of-the-art in Off-Target prediction, highlighting the efficacy of our approach. Furthermore, leveraging the power of the integrated gradient method, we make an effort to interpret our models resulting in a detailed analysis and understanding of the underlying factors that contribute to Off-Target predictions, in particular the presence of two sub-regions in the seed region of sgRNA which extends the established biological hypothesis of Off-Target effects. To the best of our knowledge, our model can be considered as the first model combining high efficacy, interpretability, and a desirable balance between precision and recall.
Selective ablation of thymic and peripheral Foxp3+ regulatory T cell development

Foxp3+ Treg cells of thymic (tTreg) and peripheral (pTreg) developmental origin are thought to synergistically act to ensure immune homeostasis, with self-reactive tTreg cells primarily constraining autoimmune responses. We exploited tTreg-specific GFP/Cre recombinase activity to selectively ablate either tTreg (ΔtTreg) or pTreg (ΔpTreg) cell development. In contrast to the tTreg cell behavior in ΔpTreg mice, pTreg cells with a highly activated suppressor phenotype replenished the Treg cell pool of C57BL/6. ΔtTreg mice, preventing early mortality and fatal autoimmunity. Even with advancing age, pTreg cells largely maintained immune tolerance in C57BL/6. ΔtTreg mice. However, only two generations of (C57BL/6>NOD) backcrossing precipitated severe disease lethality associated with a distinct, partially overlapping pattern of organ-specific autoimmunity. Genetic association studies defined a small set of autoimmune risk loci sufficient to unleash a particularly severe form of diabetes, including genes known to impinge on Treg cell biology. Thus, pTreg cells exhibit an unexpectedly high functional adaptability, emphasizing their importance as mediators of bystander effects to ensure self-tolerance. SUMMARY This study in complementary loss-of-function mouse models uncovers an unexpected functional plasticity of pTreg cells in constraining systemic autoimmune responses in the absence of tTreg cells and identifies tTreg cells as primary regulators of β-cell autoimmunity in type 1 diabetes.
XJoin: A Reactively-Scheduled Pipelined Join Operator

Wide-area distribution raises significant performance problems for traditional query processing techniques as data access becomes less predictable due to link congestion, load imbalances, and temporary outages. Pipelined query execution is a promising approach to coping with unpredictability in such environments as it allows scheduling to adjust to the arrival properties of the data. We have developed a non-blocking join operator, called XJoin, which has a small memory footprint, allowing many such operators to be active in parallel. XJoin is optimized to produce initial results quickly and can hide intermittent delays in data arrival by reactively scheduling background processing. We show that XJoin is an effective solution for providing fast query responses to users even in the presence of slow and bursty remote sources. 1 Wide-Area Query Processing The explosive growth of the Internet and the World Wide Web has made tremendous amounts of data available on-line. Emerging standards such as XML, combined with wrapper technologies address semantic challenges by providing relational-style interfaces to remote data. Beyond the issues of structure and semantics, however, there remain significant technical obstacles to building responsive, usable query processing systems for widearea environments. A key performance issue that arises in such environments is response-time unpredictability. Data access over wide-area networks involves a large number of remote data sources, intermediate sites, and communications links, all of which are vulnerable to overloading, congestion, and failures. Such problems can cause significant and unpredictable delays in the access of information from remote sources. These delays, in turn, cause traditional distributed query processing strategies to break down, resulting in unresponsive and hence, unusable systems. In previous work [AFTU96] we identified three classes of delays that can affect the responsiveness of query processing: 1) initial delay, in which there is a longer than expected wait until the first tuple arrives from a remote source; 2) slow delivery, in which data arrive at a fairly constant but slower than expected rate; and 3) bursty arrival, in which data arrive in a fluctuating manner. With traditional query processing techniques, query execution can become blocked even if only one of the accessed data sources experiences such delays. Copyright 2000 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. Bulletin of the IEEE Computer Society Technical Committee on Data Engineering This work was partially supported by the NSF under grant IRI-94-09575, by the Office of Naval Research under contract number N66001-97-C8539 (DARPA order number F475), by a Siemens Faculty Development Award, and by an IBM Partnership Award.
Constraint Problem Specification as Compression

Constraint Programming is a powerful and expressive framework for modelling and solving combinatorial problems. It is nevertheless not always easy to use, which has led to the development of high-level speciﬁcation languages. We show that Constraint Logic Programming can be used as a meta-language to describe itself more compactly at a higher level of abstraction. This can produce problem descriptions of comparable size to those in existing speciﬁcation languages, via techniques similar to those used in data compression. An advantage over existing speciﬁcation languages is that, for a problem whose speciﬁcation requires the solution of an auxiliary problem, a single speciﬁcation can unify the two problems. Moreover, using a symbolic representation of domain values leads to a natural way of modelling channelling constraints.
An Argumentation-Based Approach for Goal Reasoning and Explanations Generation

Explainable Artificial Intelligence systems, including intelligent agents, are expected to explain their internal decisions, behaviors and reasoning that produce their choices to the humans (or to other systems) with which they interact. Given this context, the aim of this article is to introduce a practical reasoning agent framework that supports generation of explanations about the goals the agent committed to. Firstly, we present an argumentation-based formalization for supporting goal reasoning. This is based on the belief-based goal processing model proposed by Castelfranchi and Paglieri, which is a more granular and refined model than the Beliefs–Desires–Intentions model. We focus on the dynamics of goals since they are desires until they become intentions, including the conditions under which a goal can be cancelled. We use formal argumentation reasoning to support the passage of the goals from their initial state until their final state. Secondly, in order that agents based on the proposed formalization be able to generate explanations about the goals they decided to commit to, we endow them with a mechanism for generating both complete and partial explanations. Finally, we use a scenario of rescue robots in order to illustrate the performance of our proposal, for which a simulator was developed to support the agents goal reasoning.
Improving the impact of Big Data Analytics Projects with Benefits Dependency Networks

Big data analytics is regarded as the next frontier in creating digital opportunities for businesses. An-alytics projects rarely deliver the intended benefits for the organisation that invest in these data analytics, and currently, no widely accepted design method for analytics projects exists. To address this, we report from an action research project in an organisation highly involved with big data analytics and how benefits materialize from these projects through the practices of tailored and focused benefits management. We argue for using the benefits dependency network for orchestrating commitment to benefits. Benefits dependency networks create linkages between analytics technology, organisational change activities, stakeholders’ interests and to-be benefits of a project. With this study, we contribute with: (1) a tailored technique for benefits dependency networks, (2) focus on benefits into established project development practices for big data analytics (3) facilitation as a key capability in developing a benefits dependency network.
Resource and Performance Prediction for Building a Next Generation Database Cloud

Cloud computing is characterized by shared infrastructure and a decoupling between its operators and tenants. These two characteristics impose new challenges to databases applications hosted in the cloud, namely: (i) how to price database services, (ii) how to isolate database tenants, and (iii) how to optimize database performance on this shared infrastructure. We argue that today’s solutions, based on virtual-machines, do not properly address these challenges. We hint at new research directions to tackle these problems and argue that these three challenges share a common need for accurate predictive models of performance and resource utilization. We present initial predictive models for the important class of OLTP/Web workloads and show how they can be used to address these challenges.
Conformational Changes Associated with Protein-Protein Interactions

Keywords: protein binding, allosteric regulation, conformational changes, induced fit, pre-existing equilibrium, dynamic population shift " Teaser " : A discussion of current articles revealing conformational changes upon protein-protein binding shows there is increasing experimental data supporting the hypothesis that unbound proteins exist in multiple conformations. Summary Motions related to protein–protein binding events can be surveyed from the perspective of the Database of Macromolecular Movements. There are a number of alternate conceptual models that describe these events, particularly induced fit and pre-existing equilibrium. There is evidence for both alternatives from recent studies of conformational change. However, there is increasing support for the pre-existing equilibrium model, whereby proteins are found to simultaneously exist in populations of diverse conformations. currently stores over 250 distinct molecular motions, most of which are based on solved structures [3]. While these conformational changes can occur upon environmental changes such as varying pH and temperature levels, the majority of large conformational movements in the database take place upon the event of binding interactions between proteins, ligands, sugars, lipids, and/or small molecules. Here we focus on protein-protein interactions and the diverse conformational changes that are observed upon protein binding. Several different models have attempted to explain protein binding mechanisms (Figure 1). The " lock and key " concept, originally introduced by Emil Fischer in 1894, assumes that one protein has a cavity or indentation that another protein perfectly fits into. These two proteins can interact with almost no change in conformations. However, this model cannot account for proteins that can bind various substrates that have a different shape from the ligand. The " induced fit " model [4] introduced by Daniel Koshland in 1958, tries to account for this by assuming that there is a certain amount of plasticity in the active site to accommodate its ligand, analogous to a hand and a glove. The ligand would induce a conformational change at the binding site, shifting it toward an active state. The pre-existing equilibrium hypothesis [5] is based on protein folding theories of the funnel energy landscape[6-9]. The native state of the protein contains an ensemble of conformations at its binding site. The ligand will bind selectively to an active conformation, thereby biasing the equilibrium toward the binding conformation. For proteins that exhibit allosteric behavior, the binding of a ligand in one area of a protein can affect the conformation of the protein at a distant region away from …
Interpolating between ordinary and bumpless pipe dreams

We introduce hybrid pipe dreams, in which some rows are specified to contain ordinary pipe dream tiles (plus a couple new ones) and some to contain bumpless pipe dream tiles (albeit upside down). For each of the 2 n possibilities of row specification, there is a sum over hybrid pipe dreams to compute each double Schubert polynomial. We give a bijection to swap the specifications on two adjacent rows, demonstrating the equivalence of the many formulæ.
Apport de la geochimie isotopique (#13c) a l'etude du renouvellement des matieres organiques et des sucres neutres dans les sols tropicaux soumis a des changements d'ecosystemes : cas des amenagements forestiers sur les savanes de pointe-noire au congo

Dans la region de pointe-noire (congo), des savanes sont amenagees en plantations de pins et d'eucalyptus. En raison de leur cycle de photosynthese different, les graminees de la savane et les arbres des plantations conferent du carbone organique des sols, une composition isotopique (#1#3c/#1#2c) differente. Les peuplements de pins et d'eucalyptus introduits a des dates differentes sur la savane, induisent dans les horizons du sol un marquage isotopique des matieres organiques qui varie avec l'age des plantations et avec la profondeur. Le marquage tres sensible en surface, permet d'approcher la dynamique du renouvellement de la matiere organique issue de la savane par celle venant des apports forestiers. Le temps de demi-vie du carbone organique initial serait de 16 annees; ce qui est l'indice d'un renouvellement rapide des matieres organiques. La mineralisation et le renouvellement des matieres organiques originelles varient selon leur nature et leur localisation. D'une matiere generale, les fractions figurees constituees en majorite de debris vegetaux se renouvellent en quelques annees alors que les substances associees aux mineraux argileux se mineralisent et se renouvellent plus lentement. Ceci serait du a une forte contribution d'argiles grossieres (kaolinite) dans les sols tropicaux developpes sur des formations superficielles detritiques. Les monomeres glucidiques solubilises a l'aide d'hydrolyses acides ont ete identifies en chromatographie en phase gazeuse et quantifies selon des methodes colorimetriques. Les sucres neutres forment un ensemble au sein duquel la distribution relative de chacun d'eux evolue avec l'age des plantations. L'evolution des monomeres glucidiques s'effectue tres rapidement des les premieres annees de plantation et tend vers 10 ans de plantation vers un etat d'equilibre apparent tant au plan quantitatif qu'au plan de la distribution de chacun d'eux. La decroissance des sucres de la savane (arabinose-fucose-galactose) et l'augmentation du xylose avec l'age des plantations constituent un indice significatif du renouvellement des matieres organiques de la savane par celles de la foret
Software Product Management

The success of a product or solution depends on effective product management. This article provides a brief overview of software product management and some experiences with introducing, improving, and deploying the role of a product manager in industry. The author found that with increasing institutionalization of a consistent and empowered product management role, project success rates in terms of schedule predictability, quality, and duration improve. Based on empirical evidence, the author provides concrete practices that will boost software product management in your company and thus your own success rates.
In press: Journal of Experimental Psychology: General Nonverbal displays of dominance and prestige: Evidence for cross-cultural and early-emerging recognition

: Two universal strategies for attaining influence – dominance , or the use of intimidation and force to obtain power, and prestige , or garnering respect by demonstrating knowledge and expertise – are communicated through distinct nonverbal displays in North America. Given evidence for the emergence and effectiveness of these strategies across cultures, including non-WEIRD small-scale, traditional societies in Africa, Asia, and South America, the nonverbal displays that are used to reliably communicate these strategies also might be universal. Here, we demonstrate that the dominance display is recognized by the Mayangna, a small-scale society in rural Nicaragua, and by Canadian children as young as 2 and 3 years old. We also find that the prestige display is reliably differentiated from dominance by both groups, and judged as a high rank signal by the Mayangna. However, members of the Mayangna confused the prestige display with happiness, and children confused the prestige display with a neutral expression. Overall, findings are consistent with a ubiquitous and early-emerging ability to recognize dominance, and with the suggestion that the prestige display is more culturally variable and ontogenetically slower to emerge.
B LACK - BOX A DVERSARIAL A TTACKS

Deep machine learning models are increasingly deployed in the wild, subject to adversarial attacks. White-box model attacks assume to have full knowledge of the deployed target models, whereas the black-box models need to infer the target model via curated labeled dataset or sending abundant data queries and launch attacks. The challenge of black-box lies in how to acquire data for querying target models and effectively learn the substitute model using a minimum number of query data, which can be real or synthetic. In this paper, we propose an effective and conﬁdent data-free black-box attack, C O DF E , which steals target model by queries of synthetically generated data. The core of our attack is a model stealing optimization consisting of two collaborating models (i) substitute model which imitates the target model and (ii) generator which generates most representative data to maximize the conﬁdence of substitute model. We propose a novel training procedure that steers the synthesizing direction based on the conﬁdence of substitute model and exploit a given set of synthetically generated images by multiple training iterations. We show the theoretical convergence of the proposed model stealing optimization and empirically evaluate its success rate on three datasets. Our results show that the accuracy of substitute models and attack success rate can be up to 56% and 34% higher than the state of the art data-free black-box attacks
Wadge Degrees of Classes of omega-Regular k-Partitions

We develop a theory of k-partitions of the set of infinite words recognizable by classes of finite automata. The theory enables to complete proofs of existing results about topological classifications of the (aperiodic) omega-regular k-partitions and provides tools for dealing with other similar questions. In particular, we characterize the structure of Wadge degrees of (aperiodic) omega-regular $k$-partitions, prove the decidability of many related problems, and discuss their complexity.
Hubungan antara Kualitas Tidur dengan Konsentrasi Belajar dan Indeks Prestasi Mahasiswa Program DIII Kebidanan STIKES 'Aisyiyah Yogyakarta

Latar Belakang: Gangguan tidur pada dewasa muda, salah satunya disebabkan karena ketidakmampuan dalam mengatur pola hidup atau aktivitas hariannya. Salah satu akibat yang ditimbulkan dari ketidakmampuan ini adalah kurang terpenuhinya kebutuhan tidur, yang disebabkan karena tidur yang kurang berkualitas. Selanjutnya kualitas tidur akan menyebabkan ketidakmampuan atau kurang optimalnya prestasi belajar karena kurang mampu berkosentrasi. Penelitian ini dilakukan untuk mengetahui hubungan antara kualitas tidur dengan kosentrasi belajar dan indeks prestasi mahasiswa Program DIII Kebidanan di STIKES ‘Aisyiyah Yogyakarta. Desain: Rancangan penelitian yang digunakan adalah penelitian deskriptif korelasional dengan pendekatan waktu cross sectional. Metode: Metode pengambilan sampel adalah dengan Proportionate Cluster Random Sampling dengan jumlah sampel sebanyak 157 orang. Untuk menilai gangguan tidur, lama waktu tidur dengan memahami kuesioner Pittsburgh Sleep Quality Index (PSQI) dan untuk mengukur tingkat kosentrasi belajar dengan memahami kuesioner Wechsler Adult Intelligence Scale (WAIS). Hasil: Terdapat hubungan antara kualitas tidur dengan konsentrasi belajar (p=0,036) dan terdapat hubungan antara kualitas tidur dengan indeks prestasi belajar mahasiswa (p=0,042).