Miracle-dz/UniFAR-FTUs huggingface dataset:
-7-Analysis of Taxi Trip Distribution Characteristics Based on GPS Data

: Taxi, as one of the important passenger transportation modes in cities, has always had the problem of imbalance between supply and demand. Analyzing the characteristics of taxi travel distribution can effectively help relevant departments realize scientific taxi dispatch, thereby solving the contradiction between supply and demand between taxis and passengers. To achieve the above goals, this article takes Beijing as an example, and analyzes the temporal and spatial distribution characteristics of taxi travel based on the GPS data of taxis in Beijing from January 1 to January 14, 2019. The research results show that: in terms of time, the total number of taxi trips on weekdays is higher than that on weekdays. The peak average total number of trips on weekdays is 14,000 passengers/h, and on weekends it is 10,000 passengers/h. Spatially, the distribution of taxi trips is consistent, mainly in core areas such as essential transportation hubs.
Churn Prediction in Customer Loyalty Program: A Case Study

Alınma: 20.11. 2019 Kabul: 25.12. 2019 Artan rekabetle birlikte, yeni müşteri edinmek her geçen gün daha maliyetli bir hale geldi ve şirketler var olan müşterilerini elde tutmak için daha fazla çaba harcar oldu. Tahminleyici modellerin geliştirilmesi ve bilgisayar teknolojisindeki gelişmeler sayesinde büyük miktarda veriyi analiz edebilme kabiliyeti, şirketlere, hangi müşterilerinin müşterileri olarak kalmaya devam edeceğini ve hangilerinin terk etmeye meyilli olabileceğini güvenilir bir şekilde tahmin etme imkanı verdi. Bu çalışmada, Türkiye'de mobil bir sadakat uygulamasından elde edilen veriler; restoran, perakende ve e-ticaret olmak üzere faaliyet gösterilen üç farklı sektör üzerinden analiz edilecektir. Müşterilerin gelecek çeyrekteki aktiflik durumlarını tahmin etmek için her sektörde iki farklı tahminleyici model geliştirilmiştir. Geliştirilen modellerde Lojistik Regresyon ve Yapay Sinir Ağları yöntemleri kullanılmıştır. Geliştirilen tüm bu altı modelde, bütün sektörlerde genel olarak %90'ın üzerinde doğruluk oranına ulaşılmasının yanı sıra, Yapay Sinir Ağları doğruluk, hassasiyet ve özgüllük ölçütleri açısından Lojistik Regresyona kıyasla daha iyi bir performans sergiledi. Anahtar Kelimeler: Müşteri Kayıp Tahmini, Sadakat Programı, Lojistik Regresyon, Yapay Sinir Ağları
Diagnostic significance of petiole anatomy in the identification of Bauhinia species (Fabaceae)

: Petiole anatomical studies were conducted on six species of Bauhinia viz., B.blakeana Dunn. , B.malabarica Roxb. , B.purpurea1 L. , B.purpurea2 L. , B.racemosa Lam. and B.tomentosa L. belonging to family Leguminosae (Fabaceae) in search of useful and stable taxonomic characters for the identification of species. Petiole showed diagnostic values that are of taxonomic importance. The result showed substantial variation in the petiole outline, thickness in cuticle, cortex main vascular regions and presence of cell inclusions. Petiole outline in B . racemosa, B. blakeana and B.purpurea1 was planoconvex, while B.malabarica, B.tomentosa and B.purpurea 2 had circular. In the main vascular region B.malabarica, B.tomentosa, B. racemosa, B.purpurea1 had two inverted medullary bundle, while B.blakeana had one inverted medullary bundle and no medullary bundle was observed in B.purpurea2. Cell inclusions were in the form of rhomboidal crystals observed in B.blakeana, B.racemosa, B.purpurea1 and spheraphides observed in B.malabarica, B.tomentosa and B.purpurea 2. Cluster analysis was done for the petiole anatomical characters of all six species of Bauhinia, in which three major clusters were observed linked to each other. A diagnostic key was made which suggests that the study provides referential anatomical information for the correct the species.
Nicholas C. Spitzer

carried out a sustained line of research originating in studies of the development of neuronal excitability. This led to the discovery, in the embryonic amphibian nervous system, of calcium-dependent action potentials that generate transient elevations of intracellular calcium before the action potentials achieve classical sodium-dependence. He found that changes in this calcium-dependent electrical activity cause neurotransmitter switching, which is associated with matching changes in postsynaptic receptors. He subsequently discovered that changes in electrical activity also drive transmitter switching and receptor matching in the adult mammalian brain. Transmitter switching often switches the sign of the synapse and leads to changes in behavior that can be detrimental or beneficial. These findings identified a novel form of plasticity, distinct from changes in synaptic weight and synapse number, and overturned the long-held view that the choice of transmitter is irreversibly specified by cell at an early stage of the action potential we used antisense cRNA xKv3.1 expression of this gene in the spinal cord. These the amplitude and rate of activation of I Kv and increased the duration of the action potential in 40 percent of the neurons, matching the expression of xKv3.1 that we had observed in cultured neurons 2000). These findings, along with Angie Ribera’s results from her lab at the of indicated that heterogeneous K + channel gene expression gives rise to homogenous I Kv current. It was satisfying to have an understanding of the development of the action potential at the level of expression of single K + channel genes. nucleus, which is important for gait and balance. The switch involved a decrease in the number of neurons expressing acetylcholine and a matching increase in the number of neurons expressing GABA. We next genetically marked cholinergic neurons to identify ones that had switched their transmitter. This method permanently labeled cholinergic neurons with mRuby2 fluorescent protein, even those that lost acetylcholine as a result of running. We could then score the number of mRuby2-labeled fluorescent neurons that expressed GABA after running. The results showed unambiguously that formerly cholinergic
Fake News Detection on the Web: A Deep Learning Based Approach

The acceptance and popularity of social media platforms for the dispersion and proliferation of news articles have led to the spread of questionable and untrusted information (in part) due to the ease by which misleading content can be created and shared among the communities. While prior research has attempted to automatically classify news articles and tweets as credible and non-credible. This work complements such research by proposing an approach that utilizes the amalgamation of Natural Language Processing (NLP), and Deep Learning techniques such as Long Short-Term Memory (LSTM). Moreover, in Information System’s paradigm, design science research methodology (DSRM) has become the major stream that focuses on building and evaluating an artifact to solve emerging problems. Hence, DSRM can accommodate deep learning-based models with the availability of adequate datasets. Two publicly available datasets that contain labeled news articles and tweets have been used to validate the proposed model’s effectiveness. This work presents two distinct experiments, and the results demonstrate that the proposed model works well for both long sequence news articles and short-sequence texts such as tweets. Finally, the findings suggest that the sentiments, tagging, linguistics, syntactic, and text embeddings are the features that have the potential to foster fake news detection through training the proposed model on various dimensionality to learn the contextual meaning of the news content.
A conditional limit theorem for generalized diffusion processes

Let X = { X ( t ) : t ≥ 0 } be a one-dimensional generalized diﬀusion process with initial state X (0) > 0, hitting time τ X (0) at the origin and speed measure m which is regularly varying at inﬁnity with exponent 1 /α − 1 > 0. It is proved that, for a suitable function u ( c ), the probability law of { u ( c ) − 1 X ( ct ) : 0 < t ≤ 1 } conditioned by { τ X (0) > c } converges as c → ∞ to the conditioned 2(1 − α )-dimensional Bessel excursion on natural scale and that the latter is equivalent to the 2(1 − α )-dimensional Bessel meander up to a scale transformation. In particular, the distribution of u ( c ) − 1 X ( c ) converges to the Weibull distribution. From the conditional limit theorem we also derive a limit theorem for some of regenerative process associated with X .
Reserpine maintains photoreceptor survival in retinal ciliopathy by resolving proteostasis imbalance and ciliogenesis defects

Ciliopathies manifest from sensory abnormalities to syndromic disorders with multiorgan pathologies, with retinal degeneration a highly penetrant phenotype. Photoreceptor cell death is a major cause of incurable blindness in retinal ciliopathies. To identify drug candidates to maintain photoreceptor survival, we performed an unbiased, high-throughput screening of over 6,000 bioactive small molecules using retinal organoids differentiated from induced pluripotent stem cells (iPSC) of rd16 mouse, which is a model of Leber congenital amaurosis (LCA)10 caused by mutations in the cilia-centrosomal gene CEP290. We identified five non-toxic positive hits, including the lead molecule reserpine, which improved photoreceptor survival in rd16 organoids. Reserpine also maintained photoreceptors in retinal organoids derived from induced pluripotent stem cells of LCA10 patients and in rd16 mouse retina in vivo. Reserpine-treated patient organoids revealed modulation of signaling pathways related to cell survival/death, metabolism, and proteostasis. Further investigation uncovered misregulation of autophagy associated with compromised primary cilium biogenesis in patient organoids and rd16 mouse retina. Reserpine partially restored the balance between autophagy and the ubiquitin-proteasome system, at least in part by increasing the cargo adaptor p62 and improving primary cilium assembly. Our study identifies effective drug candidates in preclinical studies of CEP290 retinal ciliopathies through cross-species drug discovery using iPSC-derived organoids, highlights the impact of proteostasis in the pathogenesis of ciliopathies, and provides new insights for treatments of retinal neurodegeneration.
Negation, Coordination, and Quantifiers in Contextualized Language Models

With the success of contextualized language models, much research explores what these models really learn and in which cases they still fail. Most of this work focuses on specific NLP tasks and on the learning outcome. Little research has attempted to decouple the models’ weaknesses from specific tasks and focus on the embeddings per se and their mode of learning. In this paper, we take up this research opportunity: based on theoretical linguistic insights, we explore whether the semantic constraints of function words are learned and how the surrounding context impacts their embeddings. We create suitable datasets, provide new insights into the inner workings of LMs vis-a-vis function words and implement an assisting visual web interface for qualitative analysis.
Time symmetry in quantum theories and beyond

There is a stark tension among different formulations of quantum theory in that some are fundamentally time-symmetric and others are radically time-asymmetric. This tension is crisply captured when thinking of physical theories as theories of processes. We review process theories and their diagrammatic representation, and show how quantum theory can be described in this language. The tension between time-symmetry and time-asymmetry is then captured by the tension between two of the key structures that are used in this framework. On the one hand, the symmetry is captured by a dagger structure, which is represented by a reflection of diagrams. On the other hand, the asymmetry is captured by a condition involving discarding which, ultimately, is responsible for the theory being compatible with relativistic causality. Next we consider three different ways in which we this tension can be resolved. The first of these is closely related to recent work of Lucien Hardy, where the tension is resolved by adding in a time reversed version of discarding together with a suitable consistency condition. The second is, to our knowledge, a new approach. Here the tension is resolved by adding in new systems which propagate backwards in time, and imposing a consistency condition to avoid running into well known time-travel paradoxes. The final approach that we explore is closely related to work of Oreshkov and Cerf, where the tension is resolved by removing the constraint associated with discarding. We show two equivalent ways in which this can be done whilst ensuring that the resulting theory still makes sensible operational predictions.
Dynamic fibronectin assembly and remodeling by leader neural crest cells prevents jamming in collective cell migration

Collective cell migration plays an essential role in vertebrate development, yet the extent to which dynamically changing microenvironments influence this phenomenon remains unclear. Observations of the distribution of the extracellular matrix (ECM) component fibronectin during the migration of loosely connected neural crest cells (NCCs) lead us to hypothesize that NCC remodeling of an initially punctate ECM creates a scaffold for trailing cells, enabling them to form robust and coherent stream patterns. We evaluate this idea in a theoretical setting by developing an individual-based computational model that incorporates reciprocal interactions between NCCs and their ECM. ECM remodeling, haptotaxis, contact guidance, and cell-cell repulsion are sufficient for cells to establish streams in silico, however, additional mechanisms, such as chemotaxis, are required to consistently guide cells along the correct target corridor. Further model investigations imply that contact guidance and differential cell-cell repulsion between leader and follower cells are key contributors to robust collective cell migration by preventing stream breakage. Global sensitivity analysis and simulated gain- and loss-of-function experiments suggest that long-distance migration without jamming is most likely to occur when leading cells specialize in creating ECM fibers, and trailing cells specialize in responding to environmental cues by upregulating mechanisms such as contact guidance.
History-deterministic Parikh Automata

Parikh automata extend finite automata by counters that can be tested for membership in a semilinear set, but only at the end of a run. Thereby, they preserve many of the desirable properties of finite automata. Deterministic Parikh automata are strictly weaker than nondeterministic ones, but enjoy better closure and algorithmic properties. This state of affairs motivates the study of intermediate forms of nondeterminism. Here, we investigate history-deterministic Parikh automata, i.e., automata whose nondeterminism can be resolved on the fly. This restricted form of nondeterminism is well-suited for applications which classically call for determinism, e.g., solving games and composition. We show that history-deterministic Parikh automata are strictly more expressive than deterministic ones, incomparable to unambiguous ones, and enjoy almost all of the closure properties of deterministic automata.
Conditional H i Mass Functions and the H i-to-halo Mass Relation in the Local Universe

We present a new H i mass estimator that relates log10 (M HI/M *) to a linear combination of four galaxy properties: stellar surface mass density, color index u − r, stellar mass, and concentration index, with the scatter of individual galaxies around the mean H i mass modeled with a Gaussian distribution function. We calibrate the estimator using the xGASS sample, including both H i detection and nondetection, and constrain the model parameters through Bayesian inferences. Tests with mock catalogs demonstrate that our estimator provides unbiased H i masses for optical samples like SDSS. We apply our estimator to the SDSS spectroscopic sample to estimate the H i mass function (HIMF) of local galaxies, as well as the conditional H i mass function in galaxy groups and the H i–halo mass relation. Our HIMF agrees with the ALFALFA measurements at M HI ≳ 5 × 109 M ⊙, but with higher amplitude and a steeper slope at lower masses. We show that this discrepancy is caused primarily by the cosmic variance, which is corrected for the SDSS sample but not for ALFALFA. The total CHIMFs for all halo masses can be described by a single Schechter function, while those of central galaxies show a double-Gaussian profile. The total H i mass in a group increases monotonically with halo mass, but for central galaxies, the H i mass shows weak dependence on halo mass when M h ≳ 1012 M ☉. The observed H i–halo mass relation is not reproduced by current hydrodynamic simulations and semianalytic models of galaxy formation.
On Deformations of Generalized Complex Structures: the Generalized Calabi-Yau Case

We prove an analog of the Tian-Todorov theorem for twisted generalized Calabi-Yau manifolds; namely, we show that the moduli space of generalized complex structures on a compact twisted generalized Calabi-Yau manifold is unobstructed and smooth. We also construct the extended moduli space and study its Frobenius structure. The physical implications are also discussed.
On the Generic Capacity of K-User Symmetric Linear Computation Broadcast

Linear computation broadcast (LCBC) refers to a setting with $d$ dimensional data stored at a central server, where $K$ users, each with some prior linear side-information, wish to retrieve various linear combinations of the data. The goal is to determine the minimum amount of information that must be broadcast to satisfy all the users. The reciprocal of the optimal broadcast cost is the capacity of LCBC. The capacity is known for up to $K=3$ users. Since LCBC includes index coding as a special case, large $K$ settings of LCBC are at least as hard as the index coding problem. Instead of the general setting (all instances), by focusing on the generic setting (almost all instances) this work shows that the generic capacity of the symmetric LCBC (where every user has $m'$ dimensions of side-information and $m$ dimensions of demand) for large number of users ($K>d$ suffices) is $C_g=1/\Delta_g$, where $\Delta_g=\min\left\{\max\{0,d-m'\}, \frac{dm}{m+m'}\right\}$, is the broadcast cost that is both achievable and unbeatable asymptotically almost surely for large $n$, among all LCBC instances with the given parameters $p,K,d,m,m'$. Relative to baseline schemes of random coding or separate transmissions, $C_g$ shows an extremal gain by a factor of $K$ as a function of number of users, and by a factor of $\approx d/4$ as a function of data dimensions, when optimized over remaining parameters. For arbitrary number of users, the generic capacity of the symmetric LCBC is characterized within a factor of $2$.
Ferroelectricity and resistive switching in BaTiO$_3$ thin films with liquid electrolyte top contact for bioelectronic devices

We investigate ferroelectric- and resistive switching behavior in 18-nm-thick epitaxial BaTiO$_3$ (BTO) films in a model electrolyte-ferroelectric-semiconductor (EFS) configuration. The system is explored for its potential as a ferroelectric microelectrode in bioelectronics. The BTO films are grown by pulsed laser deposition (PLD) on semiconducting Nb-doped (0.5 wt\%) SrTiO$_{3}$ (Nb:STO) single crystal substrates. The ferroelectric properties of the bare BTO films are demonstrated by piezoresponse force microscopy (PFM) measurements. Cyclic voltammetry (CV) measurements in EFS configuration, with phosphate buffered saline (PBS) acting as the liquid electrolyte top contact, indicate characteristic ferroelectric switching peaks in the bipolar current-voltage loop. The ferroelectric nature of the observed switching peaks is confirmed by analyzing the current response of the EFS devices to unipolar voltage signals. Moreover, electrochemical impedance spectroscopy (EIS) measurements indicate bipolar resisitive switching behavior of the EFS devices, which is controlled by the remanent polarization state of the BTO layer. Our results represent a constitutive step towards the realization of neuroprosthetic implants and hybrid neurocomputational systems based on ferroelectric microelectrodes.
Exact Exponents for Concentration and Isoperimetry in Product Polish Spaces

In this paper, we derive variational formulas for the asymptotic exponents of the concentration and isoperimetric functions in the product Polish probability space. These formulas are expressed in terms of relative entropies (which are from information theory) and optimal transport cost functionals (which are from optimal transport theory). Our results verify an intimate connection among information theory, optimal transport, and concentration of measure or isoperimetric inequalities. In the concentration regime, the corresponding variational formula is in fact a dimension-free bound on the exponent of the concentration function. The proofs in this paper are based on information-theoretic and optimal transport techniques. Our results generalize Alon, Boppana, and Spencer’s in [4], Gozlan and Léonard’s [14], and Ahlswede and Zhang’s in [3].
The Shastry-Sutherland Compound SrCu2(BO3)2 Studied up to the Saturation Magnetic Field

T. Nomura, ∗ P. Corboz, † A. Miyata, S. Zherlitsyn, Y. Ishii, Y. Kohama, Y. H. Matsuda, A. Ikeda, C. Zhong, ‡ H. Kageyama, and F. Mila Institute for Solid State Physics, University of Tokyo, Kashiwa, Chiba 277-8581, Japan Institute for Theoretical Physics and Delta Institute for Theoretical Physics, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands Hochfeld-Magnetlabor Dresden (HLD-EMFL), Helmholtz-Zentrum Dresden-Rossendorf, 01328 Dresden, Germany Department of Engineering Science, University of Electro-Communications, Chofu, Tokyo 182-8585, Japan Graduate School of Engineering, Kyoto University. Nishikyouku, Kyoto 615-8510, Japan Institute of Theoretical Physics, Ecole Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland (Dated: September 19, 2022)
SQ-Swin: a Pretrained Siamese Quadratic Swin Transformer for Lettuce Browning Prediction

—Enzymatic browning is a major quality defect of packaged “ready-to-eat” fresh-cut lettuce salads. While there have been many research and breeding efforts to counter this problem, progress is hindered by the lack of a technology to identify and quantify browning rapidly, objectively, and reliably. Here, we report a deep learning model for lettuce browning prediction. To the best of our knowledge, it is the ﬁrst-of-its- kind on deep learning for lettuce browning prediction using a pretrained Siamese Quadratic Swin (SQ-Swin) transformer with several highlights. First, our model includes quadratic features in the transformer model which is more powerful to incorporate real world representations than the linear transformer. Second, a multi-scale training strategy is proposed to augment the data and explore more of the inherent self-similarity of the lettuce images. Third, the proposed model uses a siamese architecture which learns the inter-relations among the limited training samples. Fourth, the model is pretrained on the ImageNet and then trained with the reptile meta-learning algorithm to learn higher-order gradients than a regular one. Experiment results on the fresh-cut lettuce datasets show that the proposed SQ-Swin outperforms the traditional methods and other deep learning-based backbones.