cssi/SciSciGPT-SciSciNet huggingface dataset:
Financial Repression is Knocking at the Door, Again

Financial repression (legal restrictions on interest rates, credit allocation, capital movements, and other financial operations) was widely used in the past but was largely abandoned in the liberalization wave of the 1990s, as widespread support for interventionist policies gave way to a renewed conception of government as an impartial referee. Financial repression has come back on the agenda with the surge in public debt in the wake of the Global Financial Crisis, and some countries have reintroduced administrative ceilings on interest rates. By distorting market incentives and signals, financial repression induces losses from inefficiency and rent-seeking that are not easily quantified. This study attempts to assess some of these losses by estimating the impact of financial repression on growth using an updated index of interest rate controls covering 90 countries over 45 years. The results suggest that financial repression poses a significant drag on growth, which could amount to 0.4-0.7 percentage points.
Compact spaces with a P-base

Abstract In the paper, we investigate (scattered) compact spaces with a P -base for some poset P . More specifically, we prove that any compact space with an ω ω -base is metrizable and any scattered compact space with an ω ω -base is countable under the assumption ω 1 b . These give positive solutions to Problems 8.6.9 and 8.7.7 in Banakh (2019). Using forcing, we also prove that in a model of ω 1 b , there is a non-first-countable compact space with a P -base for some poset P with calibre ω 1 .
Self-Interference Channel Characterization in Underwater Acoustic In-Band Full-Duplex Communications Using OFDM

Due to the limited available bandwidth and dynamic channel, data rates are extremely limited in underwater acoustic (UWA) communications. Addressing this concern, in-band full-duplex (IBFD) has the potential to double the efficiency in a given bandwidth. In an IBFD scheme, transmission and reception are performed simultaneously in the same frequency band. However, in UWA-IBFD, because of reflections from the surface and bottom and the inhomogeneity of the water, a significant part of the transmitted signal returns back to the IBFD receiver. This signal contaminates the desired signal from the remote end and is known as the self-interference (SI). With an estimate of the self-interference channel impulse response (SCIR), a receiver can estimate and eliminate the SI. A better understanding of the statistical characteristics of the SCIR is necessary for an accurate SI cancellation. In this article, we use an orthogonal frequency division multiplexing (OFDM) signal to characterize the SCIR in a lake water experiment. To verify the results, SCIR estimation is performed by using estimators in both the frequency and time domains. We show that, in our experiment, regardless of the depth of hydrophone, the direct path of SCIR is strong, stable and easily tracked; however, the reflection paths are weaker and rapidly time-varying making SI cancellation challenging. Among the reflections, the first bounce from the water surface is the prevalent path with a short coherence time around 70 ms.
Quadratic twists of elliptic curves and class numbers

Abstract For positive rank r elliptic curves E ( Q ) , we employ ideal class pairings E ( Q ) × E − D ( Q ) → CL ( − D ) , for quadratic twists E − D ( Q ) with a suitable “small y-height” rational point, to obtain explicit class number lower bounds that improve on earlier work by the authors. For the curves E ( a ) : y 2 = x 3 − a , with rank r ( a ) , this gives h ( − D ) ≥ 1 10 ⋅ | E tor ( Q ) | R Q ( E ) ⋅ π r ( a ) 2 2 r ( a ) Γ ( r ( a ) 2 + 1 ) ⋅ log ⁡ ( D ) r ( a ) 2 log ⁡ log ⁡ D , representing a general improvement to the classical lower bound of Goldfeld, Gross and Zagier when r ( a ) ≥ 3 . We prove that the number of twists E − D ( a ) ( Q ) with such a suitable point (resp. with such a point and rank ≥2 under the Parity Conjecture) is ≫ a , e X 1 2 − e . We give infinitely many cases where r ( a ) ≥ 6 . These results can be viewed as an analogue of the classical estimate of Gouvea and Mazur for the number of rank ≥2 quadratic twists, where in addition we obtain “log-power” improvements to the Goldfeld-Gross-Zagier class number lower bound.
Graph-based Multilingual Product Retrieval in E-Commerce Search

Nowadays, with many e-commerce platforms conducting global business, e-commerce search systems are required to handle product retrieval under multilingual scenarios. Moreover, comparing with maintaining per-country specific e-commerce search systems, having an universal system across countries can further reduce the operational and computational costs, and facilitate business expansion to new countries. In this paper, we introduce an universal end-to-end multilingual retrieval system, and discuss our learnings and technical details when training and deploying the system to serve billion-scale product retrieval for e-commerce search. In particular, we propose a multilingual graph attention based retrieval network by leveraging recent advances in transformer-based multilingual language models and graph neural network architectures to capture the interactions between search queries and items in e-commerce search. Offline experiments on five countries data show that our algorithm outperforms the state-of-the-art baselines by 35% recall and 25% mAP on average. Moreover, the proposed model shows significant increase of conversion/revenue in online A/B experiments and has been deployed in production for multiple countries.
An integrated system for predicting students’ academic performance in smart universities

Due to the current situation with Coronavirus (COVID-19) the attendance of students in the academic life has changed and the educational process has been driven towards smart educational environments. Higher educational Institutes invest significant resources in reforming their educational programs so that it will support distance learning using asynchronous or synchronous methodologies and tools. In this work, we propose the development of a student profile using data from both asynchronous and synchronous e-learning platforms, using a multi-layered neural network in order to classify students’ performance. A neural network is compared against Support Vector Machines, k-Nearest Neighbour and decision trees. The results indicate that the Neural network achieves better accuracy than the others, so using our methodology the instructors or the policy makers of the institute will be able to keep informed about the performance of the students, or take the appropriate actions in order to prevent student failure or low participation.
Tumor secreted extracellular vesicles regulate T-cell costimulation and can be manipulated to induce tumor specific T-cell responses.

Background & Aims Colorectal cancer is a major cause of cancer-related deaths worldwide. Immune checkpoint blockade therapies are effective in 30%–60% of the microsatellite instable–high subtype. Unfortunately, most patients with colorectal cancer (>85%) have microsatellite stable tumors that do not respond. In this study, we aimed to decipher the underlying tumor-intrinsic mechanisms critical for improving immunotherapy in colorectal cancer. Methods We used human and mouse tumor samples, cell lines, human colorectal cancer organoids, and various syngeneic orthotopic mouse models of late-stage colorectal cancer to define the effects of tumor cell–secreted extracellular vesicles (EVs) on antitumor immune response. Results Our analyses of human colorectal cancer immune profiles and tumor–immune cell interactions showed that tumor-secreted EVs containing microRNA miR-424 suppressed the CD28-CD80/86 costimulatory pathway in tumor-infiltrating T cells and dendritic cells, leading to immune checkpoint blockade resistance. Modified tumor-secreted EVs with miR-424 knocked down enhanced T-cell–mediated antitumor immune response in colorectal cancer tumor models and increased the immune checkpoint blockade response. Intravenous injections of modified tumor-secreted EVs induced tumor antigen–specific immune responses and boosted the immune checkpoint blockade efficacy in colorectal cancer models that mimic aggressively progressing, late-stage disease. Conclusions Collectively, we show a critical role for tumor-secreted EVs in antitumor immune regulation and immunotherapy response, which could be developed as a novel treatment for immune checkpoint blockade–resistant colorectal cancer.
Did they answer? Subjective acts and intents in conversational discourse

Discourse signals are often implicit, leaving it up to the interpreter to draw the required inferences. At the same time, discourse is embedded in a social context, meaning that interpreters apply their own assumptions and beliefs when resolving these inferences, leading to multiple, valid interpretations. However, current discourse data and frameworks ignore the social aspect, expecting only a single ground truth. We present the first discourse dataset with multiple and subjective interpretations of English conversation in the form of perceived conversation acts and intents. We carefully analyze our dataset and create computational models to (1) confirm our hypothesis that taking into account the bias of the interpreters leads to better predictions of the interpretations, (2) and show disagreements are nuanced and require a deeper understanding of the different contextual factors. We share our dataset and code at http://github.com/elisaF/subjective_discourse.
Wind speed inference from environmental flow–structure interactions

This study aims to leverage the relationship between fluid dynamic loading and resulting structural deformation to infer the incident flow speed from measurements of time-dependent structure kinematics. Wind tunnel studies are performed on cantilevered cylinders and trees. Tip deflections of the wind-loaded structures are captured in time series data, and a physical model of the relationship between force and deflection is applied to calculate the instantaneous wind speed normalized with respect to a known reference wind speed. Wind speeds inferred from visual measurements showed consistent agreement with ground truth anemometer measurements for different cylinder and tree configurations. These results suggest an approach for non-intrusive, quantitative flow velocimetry that eliminates the need to directly visualize or instrument the flow itself.
Hayek's road to serfdom

The work of Hayek, in contrast with the Marxist-Socialist-Interventionist-Galbraithian paradigm that held sway in the mid-twentieth century, appears as a beacon for free enterprise amid a sea of totalitarianism. When considered in comparison to the writings against which he contended, Hayek’s was a lonely voice, crying in the wilderness for freedom; he stood, like the Dutch boy, with his finger in the dike of onrushing statism. But if one weighs his output against that of free enterprise advocates who came later, or, better yet, against an ideal of laissez-faire capitalism, then one must categorize Hayek as lukewarm, at best, in his support of this system. This is a rather surprising thesis, even a paradoxical one, in view of the fact that 1994 was the 50th anniversary of Hayek’s Road to Serfdom, a book widely (and accurately!) credited with turning away from socialism the political thinking of an entire generation. It is therefore incumbent upon an author, such as myself, who makes such a claim, to offer evidence in support of it. Let us consider the record.
Optimal Sensor and Actuator Selection using Balanced Model Reduction

Optimal sensor and actuator selection is a central challenge in high-dimensional estimation and control. Nearly all subsequent control decisions are affected by these sensor and actuator locations. In this work, we exploit balanced model reduction and greedy optimization to efficiently determine sensor and actuator placements that optimize observability and controllability. In particular, we determine locations that optimize scalar measures of observability and controllability via greedy matrix QR pivoting on the dominant modes of the direct and adjoint balancing transformations. Pivoting runtime scales linearly with the state dimension, making this method tractable for high-dimensional systems. The results are demonstrated on the linearized Ginzburg-Landau system, for which our algorithm approximates known optimal placements computed using costly gradient descent methods.
Maternal Piwi Regulates Primordial Germ Cell Development to Ensure the Fertility of Female Progeny in Drosophila.

In many animals, germline development is initiated by proteins and RNAs that are expressed maternally. PIWI proteins and their associated small noncoding PIWI-interacting RNAs (piRNAs), which guide PIWI to target RNAs by base-pairing, are among the maternal components deposited into the germline of the Drosophila early embryo. Piwi has been extensively studied in the adult ovary and testis, where it is required for transposon suppression, germline stem cell self-renewal, and fertility. Consequently, loss of Piwi in the adult ovary using piwi-null alleles or knockdown from early oogenesis results in complete sterility, limiting investigation into possible embryonic functions of maternal Piwi. In this study, we show that the maternal Piwi protein persists in the embryonic germline through gonad coalescence, suggesting that maternal Piwi can regulate germline development beyond early embryogenesis. Using a maternal knockdown strategy, we find that maternal Piwi is required for the fertility and normal gonad morphology of female, but not male, progeny. Following maternal piwi knockdown, transposons were mildly derepressed in the early embryo but were fully repressed in the ovaries of adult progeny. Furthermore, the maternal piRNA pool was diminished, reducing the capacity of the PIWI/piRNA complex to target zygotic genes during embryogenesis. Examination of embryonic germ cell proliferation and ovarian gene expression showed that the germline of female progeny was partially masculinized by maternal piwi knockdown. Our study reveals a novel role for maternal Piwi in the germline development of female progeny and suggests that the PIWI/piRNA pathway is involved in germline sex determination in Drosophila.
LIQA: long-read isoform quantification and analysis

Long-read RNA sequencing (RNA-seq) technologies can sequence full-length transcripts, facilitating the exploration of isoform-specific gene expression over short-read RNA-seq. We present LIQA to quantify isoform expression and detect differential alternative splicing (DAS) events using long-read direct mRNA sequencing or cDNA sequencing data. LIQA incorporates base pair quality score and isoform-specific read length information in a survival model to assign different weights across reads, and uses an expectation-maximization algorithm for parameter estimation. We apply LIQA to long-read RNA-seq data from the Universal Human Reference, acute myeloid leukemia, and esophageal squamous epithelial cells and demonstrate its high accuracy in profiling alternative splicing events.
D2S: Document-to-Slide Generation Via Query-Based Text Summarization

Presentations are critical for communication in all areas of our lives, yet the creation of slide decks is often tedious and time-consuming. There has been limited research aiming to automate the document-to-slides generation process and all face a critical challenge: no publicly available dataset for training and benchmarking. In this work, we first contribute a new dataset, SciDuet, consisting of pairs of papers and their corresponding slides decks from recent years’ NLP and ML conferences (e.g., ACL). Secondly, we present D2S, a novel system that tackles the document-to-slides task with a two-step approach: 1) Use slide titles to retrieve relevant and engaging text, figures, and tables; 2) Summarize the retrieved context into bullet points with long-form question answering. Our evaluation suggests that long-form QA outperforms state-of-the-art summarization baselines on both automated ROUGE metrics and qualitative human evaluation.
Vertex-centric Parallel Computation of SQL Queries

We present a scheme for parallel execution of SQL queries on top of any vertex-centric BSP graph processing engine. The scheme comprises a graph encoding of relational instances and a vertex program specification of our algorithm called TAG-join, which matches the theoretical communication and computation complexity of state-of-the-art join algorithms. When run on top of the vertex-centric TigerGraph database engine on a single multi-core server, TAG-join exploits thread parallelism and is competitive with (and often outperforms) reference RDBMSs on the TPC benchmarks they are traditionally tuned for. In a distributed cluster, TAG-join outperforms the popular Spark SQL engine.
Future payload isolation and pointing system technology

An overview is presented of the technology associated with the precision pointing of future spaceborne science instruments. High-level architectural options for dealing with the precision pointing problem are considered, and a representative NASA mission set for the 1990s is given. Pointing accuracy and stability requirements are extracted from the mission requirements, with the sub-0.1 arcsec stability requirement emerging as the primary driver. The state of the art of current technology is assessed, including an evaluation of gimbal systems, suspension systems, and actuator and sensor component technology. Areas where the technology needs to be pushed to satisfy future requirements are identified, and some promising design options are proposed.
Ultraviolet effects on conductive coated coverglasses

Experiments on the International Sun-Earth Explorer required that the outer surface of the spacecraft be conductive. For the solar panels this was accomplished by using solar cell coverglasses coated with indium-oxide and interconnected to ground. This paper presents results of ultraviolet tests performed as part of the overall qualification program for cell assemblies using these coverglasses. The samples were exposed under vacuum at a controlled temperature to 5000 equivalent sun hours. Coverglass transmission curves and cell assembly current-voltage curves were measured before and after the test. Observed degradations were of the order of 1 percent more for conductively coated coverglasses than for coverglasses without conductive coatings.
Predicting Livelihood Indicators from Community-Generated Street-Level Imagery.

Major decisions from governments and other large organizations rely on measurements of the populace's well-being, but making such measurements at a broad scale is expensive and thus infrequent in much of the developing world. We propose an inexpensive, scalable, and interpretable approach to predict key livelihood indicators from public crowd-sourced street-level imagery. Such imagery can be cheaply collected and more frequently updated compared to traditional surveying methods, while containing plausibly relevant information for a range of livelihood indicators. We propose two approaches to learn from the street-level imagery: (1) a method that creates multi-household cluster representations by detecting informative objects and (2) a graph-based approach that captures the relationships between images. By visualizing what features are important to a model and how they are used, we can help end-user organizations understand the models and offer an alternate approach for index estimation that uses cheaply obtained roadway features. By comparing our results against ground data collected in nationally-representative household surveys, we demonstrate the performance of our approach in accurately predicting indicators of poverty, population, and health and its scalability by testing in two different countries, India and Kenya. Our code is available at https://github.com/sustainlab-group/mapillarygcn.
New quantum oscillations in current driven small junctions

The response of current-biased Josephson and normal tunnel junctions (JJs and NTJs) such as those fabricated by Voss and Webb (1981) is predicted from a quantum-mechanical description based on the observation that the response of a current-driven open system is equivalent to that of a closed system subject to an external time-dependent voltage bias. Phenomena expected include voltage oscillations with no dc voltage applied, inverse Shapiro steps of dc voltage in the presence of microwave radiation, voltage oscillation in a JJ and an NTJ coupled by a capacitance to a current-biased junction, JJ voltage oscillation frequency = I/e rather than I/2e, and different NTJ resistance than in the voltage-driven case. The effects require approximate experimental parameter values Ic = 15 nA, C = 1 fF, and T much less than 0.4 K for JJs and Ic = a few nA, C = 1 fF, and R = 3 kiloohms for 100-microV inverse Shapiro steps at 10 GHz in NTJs.
Wide-Baseline Relative Camera Pose Estimation with Directional Learning

Modern deep learning techniques that regress the relative camera pose between two images have difficulty dealing with challenging scenarios, such as large camera motions resulting in occlusions and significant changes in perspective that leave little overlap between images. These models continue to struggle even with the benefit of large supervised training datasets. To address the limitations of these models, we take inspiration from techniques that show regressing keypoint locations in 2D and 3D can be improved by estimating a discrete distribution over keypoint locations. Analogously, in this paper we explore improving camera pose regression by instead predicting a discrete distribution over camera poses. To realize this idea, we introduce DirectionNet, which estimates discrete distributions over the 5D relative pose space using a novel parameterization to make the estimation problem tractable. Specifically, DirectionNet factorizes relative camera pose, specified by a 3D rotation and a translation direction, into a set of 3D direction vectors. Since 3D directions can be identified with points on the sphere, DirectionNet estimates discrete distributions on the sphere as its output. We evaluate our model on challenging synthetic and real pose estimation datasets constructed from Matterport3D and InteriorNet. Promising results show a near 50% reduction in error over direct regression methods.
Negative Overgeneralization is Associated with Anxiety and Mechanisms of Pattern Completion in Peripubertal Youth.

This study examines neural mechanisms of negative overgeneralization, the increased likelihood of generalizing negative information, in peri-puberty. Theories suggest that weak pattern separation (overlapping representations are made distinct, indexed by DG/CA3 hippocampal subfield activation) underlies negative overgeneralization. We alternatively propose that neuro-maturational changes that favor pattern completion (cues reinstate stored representations, indexed by CA1 activation) are modulated by circuitry involved in emotional responding (amygdala, medial prefrontal cortices [mPFC]) to drive negative overgeneralization. Youth (N=34, 9-14 years) recruited from community and clinic settings participated in an emotional mnemonic similarity task while undergoing MRI. At Study, participants indicated the valence of images; at Test, participants made recognition memory judgments. Critical lure stimuli, that were similar to images at Study, were presented at Test, and errors ("false alarms") to negative relative to neutral stimuli reflected negative overgeneralization. Negative overgeneralization was related to greater and more similar patterns of activation in CA1 and both dorsal and ventral mPFC for negative relative to neutral stimuli. At Study, amygdala exhibited greater functional coupling with CA1 and dorsal mPFC during negative items that were later generalized. Negative overgeneralization is rooted in amygdala and mPFC modulation at encoding and pattern completion at retrieval.
Diagrams in the mod p cohomology of Shimura curves

We prove a local-global compatibility result in the mod $p$ Langlands program for $\mathrm{GL}_2(\mathbf{Q}_{p^f})$. Namely, given a global residual representation $\bar{r}$ that is sufficiently generic at $p$, we prove that the diagram occurring in the corresponding Hecke eigenspace of completed cohomology is determined by the restrictions of $\bar{r}$ to decomposition groups at $p$. If these restrictions are moreover semisimple, we show that the $(\varphi,\Gamma)$-modules attached to this diagram by Breuil give, under Fontaine's equivalence, the tensor inductions of the duals of the restrictions of $\bar{r}$ to decomposition groups at $p$.
Identifying Entangled Physics Relationships Through Sparse Matrix Decomposition to Inform Plasma Fusion Design

A sustainable burn platform through inertial confinement fusion (ICF) has been an ongoing challenge for over 50 years. Mitigating engineering limitations and improving the current design involves an understanding of the complex coupling of physical processes. While sophisticated simulation codes are used to model ICF implosions, these tools contain necessary numerical approximation but miss physical processes that limit predictive capability. Identification of relationships between controllable design inputs to ICF experiments and measurable outcomes (e.g., neutron yield, neutron velocity, areal density) from performed experiments can help guide the future design of experiments and development of simulation codes, to potentially improve the accuracy of the computational models used to simulate ICF experiments. We use sparse matrix decomposition methods to identify clusters of a few related design variables. Sparse principal component analysis (SPCA) identifies groupings that are related to the physical origin of the variables (laser, hohlraum, and capsule). A variable importance analysis finds that in addition to variables highly correlated with neutron yield, such as picket power and laser energy, variables that represent a dramatic change of the ICF design, such as number of pulse steps, are also very important. The obtained sparse components are then used to train a random forest (RF) regression surrogate for predicting total yield. The RF performance on the training and testing data compares with the performance of the RF trained using all the design variables considered. This work is intended to inform design changes in future ICF experiments by augmenting the expert intuition and simulation results.
Laser-annealing Josephson junctions for yielding scaled-up superconducting quantum processors

As superconducting quantum circuits scale to larger sizes, the problem of frequency crowding proves a formidable task. Here we present a solution for this problem in fixed-frequency qubit architectures. By systematically adjusting qubit frequencies post-fabrication, we show a nearly tenfold improvement in the precision of setting qubit frequencies. To assess scalability, we identify the types of “frequency collisions” that will impair a transmon qubit and cross-resonance gate architecture. Using statistical modeling, we compute the probability of evading all such conditions, as a function of qubit frequency precision. We find that, without post-fabrication tuning, the probability of finding a workable lattice quickly approaches 0. However, with the demonstrated precisions it is possible to find collision-free lattices with favorable yield. These techniques and models are currently employed in available quantum systems and will be indispensable as systems continue to scale to larger sizes.
Chiral propulsion: The method of effective boundary conditions

We propose to apply an “effective boundary condition” method to the problem of chiral propulsion. For the case of a rotating helix moving through a fluid at a low Reynolds number, the method amounts to replacing the original helix (in the limit of small pitch) by a cylinder, but with a special kind of partial slip boundary conditions replacing the non-slip boundary conditions on the original helix. These boundary conditions are constructed to reproduce far-field velocities of the original problem and are defined by a few parameters (slipping lengths) that can be extracted from a problem in planar rather than cylindrical geometry. We derive the chiral propulsion coefficients for spirals, helicoids, helically modulated cylinders and some of their generalizations using the introduced method. In the case of spirals, we compare our results with the ones derived by Lighthill and find a very good agreement. The proposed method is general and can be applied to any helical shape in the limit of a small pitch. We have established that for a broad class of helical surfaces the dependence of the chiral propulsion on the helical angle θ is universal, χ∼ cos θ sin 2θ with the maximal propulsion achieved at the universal angle θm=tan−1(1/2)≈35.26°.
Express: Lowering the Cost of Metadata-hiding Communication with Cryptographic Privacy

Existing systems for metadata-hiding messaging that provide cryptographic privacy properties have either high communication costs, high computation costs, or both. In this paper, we introduce Express, a metadata-hiding communication system that significantly reduces both communication and computation costs. Express is a two-server system that provides cryptographic security against an arbitrary number of malicious clients and one malicious server. In terms of communication, Express only incurs a constant-factor overhead per message sent regardless of the number of users, whereas previous cryptographically-secure systems Pung and Riposte had communication costs proportional to roughly the square root of the number of users. In terms of computation, Express only uses symmetric key cryptographic primitives and makes both practical and asymptotic improvements on protocols employed by prior work. These improvements enable Express to increase message throughput, reduce latency, and consume over 100x less bandwidth than Pung and Riposte, dropping the end to end cost of running a realistic whistleblowing application by 6x.
Application of Cascade Theory to Online Systems: A Study of Email and Google Cascades

It has happened to all of us. You are driving in your car, taking a road you have driven a thousand times before, confident in your ability to reach your destination. Suddenly you see construction signs and you are forced to turn off the road and take a detour. You vaguely recall driving on this detour road several years ago but you are not exactly sure where the road takes you. You see an intersection ahead and your first instinct is to turn right at the intersection. You see two cars ahead of you who were also forced to take the detour. You watch the first car make a left; you watch the second car also take a left. You reach the intersection, you stop, and what do you do? Which way do you turn? The majority of us turn left, even though our initial hunch was to turn right. At times, following the lead of the cars in front of us proves to be a wise decision and we are thankful that those in front of us had a better sense of direction than we did. Other times, however, we all foolishly end up at a dead end and realize that because the driver of the first car turned left, all of us simply watched, assumed the driver knew something we did not, and followed. We understand in hindsight that the driver of the first car was simply guessing at which way to turn and did not possess a special knowledge of the road or a particularly keen sense of direction. Why is it that most of us follow the cars in front of us, even if following requires us to ignore our own intuition? It seems that
Inference in High-Dimensional Linear Regression via Lattice Basis Reduction and Integer Relation Detection

We consider the high-dimensional linear regression problem, where the algorithmic goal is to efficiently infer an unknown feature vector $\beta ^{*}\in \mathbb {R}^{p}$ from its linear measurements, using a small number $n$ of samples. Unlike most of the literature, we make no sparsity assumption on $\beta ^{*}$ , but instead adopt a different regularization: In the noiseless setting, we assume $\beta ^{*}$ consists of entries, which are either rational numbers with a common denominator $Q\in \mathbb {Z}^{+}$ (referred to as $Q-$ rationality); or irrational numbers taking values in a rationally independent set of bounded cardinality, known to learner; collectively called as the mixed-range assumption. Using a novel combination of the Partial Sum of Least Squares (PSLQ) integer relation detection, and the Lenstra-Lenstra-Lovasz (LLL) lattice basis reduction algorithms, we propose a polynomial-time algorithm which provably recovers a $\beta ^{*}\in \mathbb {R}^{p}$ enjoying the mixed-range assumption, from its linear measurements $Y=X\beta ^{*}\in \mathbb {R}^{n}$ for a large class of distributions for the random entries of $X$ , even with one measurement ( $n=1$ ). In the noisy setting, we propose a polynomial-time, lattice-based algorithm, which recovers a $\beta ^{*}\in \mathbb {R}^{p}$ enjoying the $Q-$ rationality property, from its noisy measurements $Y=X\beta ^{*}+W\in \mathbb {R}^{n}$ , even from a single sample ( $n=1$ ). We further establish that for large $Q$ , and normal noise, this algorithm tolerates information-theoretically optimal level of noise. We then apply these ideas to develop a polynomial-time, single-sample algorithm for the phase retrieval problem. Our methods address the single-sample ( $n=1$ ) regime, where the sparsity-based methods such as the Least Absolute Shrinkage and Selection Operator (LASSO) and the Basis Pursuit are known to fail. Furthermore, our results also reveal algorithmic connections between the high-dimensional linear regression problem, and the integer relation detection, randomized subset-sum, and shortest vector problems.
Model-based sparse coding beyond Gaussian independent model

Abstract Sparse coding aims to model data vectors as sparse linear combinations of basis elements, but a majority of related studies are restricted to continuous data without spatial or temporal structure. A new model-based sparse coding (MSC) method is proposed to provide an effective and flexible framework for learning features from different data types: continuous, discrete, or categorical, and modeling different types of correlations: spatial or temporal. The specification of the sparsity level and how to adapt the estimation method to large-scale studies are also addressed. A fast EM algorithm is proposed for estimation, and its superior performance is demonstrated in simulation and multiple real applications such as image denoising, brain connectivity study, and spatial transcriptomic imaging.
Post-operative radiation therapy for non-small cell lung cancer: A comparison of radiation therapy techniques.

Abstract Objectives Post-operative radiation therapy (PORT) in locally advanced non-small cell lung cancer (LA-NSCLC) has historically been associated with toxicity. Conformal techniques like intensity modulated radiation therapy (IMRT) have the potential to reduce acute and long-term toxicity from radiation therapy. Among patients receiving PORT for LA-NSCLC, we identified factors associated with receipt of IMRT and evaluated the association between IMRT and toxicity. Methods We queried the Surveillance, Epidemiology, and End Results (SEER)-Medicare database between January 1, 2006 to December 31, 2014 to identify patients diagnosed with Stage II or III NSCLC and who received upfront surgery and subsequent PORT. Baseline differences between patients receiving 3-dimentional conformal radiation therapy (3D-CRT) and IMRT were assessed using the chi-squared test for proportions and the t-test for means. Multivariable logistic regression was used to identify predictors of receipt of IMRT and pulmonary, esophageal, and cardiac toxicity. Propensity-score matching was employed to reduce the effect of known confounders. Results A total of 620 patients met the inclusion criteria, among whom 441 (71.2%) received 3D-CRT and 179 (28.8%) received IMRT. The mean age of the cohort was 73.9 years and 54.7% were male. The proportion of patients receiving IMRT increased from 6.2% in 2006 to 41.4% in 2014 (P Conclusion In a cohort of elderly patients, the use of IMRT in the setting of PORT for LA-NSCLC was not associated with a difference in toxicity compared to 3D-CRT. This finding suggests that outcomes from PORT may be independent of radiotherapy treatment technique.
C-H oxidation in fluorenyl benzoates does not proceed through a stepwise pathway: revisiting asynchronous proton-coupled electron transfer.

2-Fluorenyl benzoates were recently shown to undergo C–H bond oxidation through intramolecular proton transfer coupled with electron transfer to an external oxidant. Kinetic analysis revealed unusual rate-driving force relationships. Our analysis indicated a mechanism of multi-site concerted proton–electron transfer (MS-CPET) for all of these reactions. More recently, an alternative interpretation of the kinetic data was proposed to explain the unusual rate-driving force relationships, invoking a crossover from CPET to a stepwise mechanism with an initial intramolecular proton transfer (PT) (Costentin, Saveant, Chem. Sci., 2020, 11, 1006). Here, we show that this proposed alternative pathway is untenable based on prior and new experimental assessments of the intramolecular PT equilibrium constant and rates. Measurement of the fluorenyl 9-C–H pKa, H/D exchange experiments, and kinetic modelling with COPASI eliminate the possibility of a stepwise mechanism for C–H oxidation in the fluorenyl benzoate series. Implications for asynchronous (imbalanced) MS-CPET mechanisms are discussed with respect to classical Marcus theory and the quantum-mechanical treatment of concerted proton–electron transfer.
Visually induced changes in cytokine production in the chick choroid

Postnatal ocular growth is regulated by a vision-dependent mechanism that acts to minimize refractive error through coordinated growth of the ocular tissues. Of great interest is the identification of the chemical signals that control visually guided ocular growth. Here, we provide evidence that the pro-inflammatory cytokine, interleukin-6 (IL-6), may play a pivotal role in the control of ocular growth using a chicken model of myopia. Microarray, real-time RT-qPCR, and ELISA analyses identified IL-6 upregulation in the choroids of chick eyes under two visual conditions that introduce myopic defocus and slow the rate of ocular elongation (recovery from induced myopia and compensation for positive lenses). Intraocular administration of atropine, an agent known to slow ocular elongation, also resulted in an increase in choroidal IL-6 gene expression. Nitric oxide appears to directly or indirectly upregulate choroidal IL-6 gene expression, as administration of the non-specific nitric oxide synthase inhibitor, L-NAME, inhibited choroidal IL-6 gene expression, and application of a nitric oxide donor stimulated IL-6 gene and protein expression in isolated chick choroids. Considering the pleiotropic nature of IL-6 and its involvement in many biological processes, these results suggest that IL-6 may mediate many aspects of the choroidal response in the control of ocular growth.
Bayesian Deep Basis Fitting for Depth Completion With Uncertainty

In this work we investigate the problem of uncertainty estimation for image-guided depth completion. We extend Deep Basis Fitting (DBF) for depth completion within a Bayesian evidence framework to provide calibrated per-pixel variance. The DBF approach frames the depth completion problem in terms of a network that produces a set of low-dimensional depth bases and a differentiable least squares fitting module that computes the basis weights using the sparse depths. By adopting a Bayesian treatment, our Bayesian Deep Basis Fitting (BDBF) approach is able to 1) predict high-quality uncertainty estimates and 2) enable depth completion with few or no sparse measurements. We conduct controlled experiments to compare BDBF against commonly used techniques for uncertainty estimation under various scenarios. Results show that our method produces better uncertainty estimates with accurate depth prediction.
Accelerating combinatorial filter reduction through constraints

Reduction of combinatorial filters involves compressing state representations that robots use. Such optimization arises in automating the construction of minimalist robots. But exact combinatorial filter reduction is an NP-complete problem and all current techniques are either inexact or formalized with exponentially many constraints. This paper proposes a new formalization needing only a polynomial number of constraints, and characterizes these constraints in three different forms: nonlinear, linear, and conjunctive normal form. Empirical results show that constraints in conjunctive normal form capture the problem most effectively, leading to a method that outperforms the others. Further examination indicates that a substantial proportion of constraints remain inactive during iterative filter reduction. To leverage this observation, we introduce just-in-time generation of such constraints, which yields improvements in efficiency and has the potential to minimize large filters.
Self-Similar Solutions with Electro-Thermal Processes for Plasmas of Arbitrary Beta

Self-similar, magnetohydrodynamic (MHD) solutions are developed for a cold planar wall next to a hot plasma with an embedded magnetic field parallel to the wall, including the relevant electro-thermal terms. Velikovich et al., [1] studied the Nernst effect in the induction equation for such a problem under the assumption that the ratio of thermal to magnetic pressure $(\beta)$ was large. Other electro-thermal processes, such as Ettingshausen, Joule heating, and Nernst-thermal heating vary inversely with $\beta$ . To study all these we have extended the self-similar formulation to allow for an arbitrary $\beta$ . The self-similar ansatz requires constant total pressure, thermal plus magnetic. Four self-similar solutions are presented with the same density and temperature boundary conditions: two of high $\beta$ and two of low $\beta,$ and for each of these with and without electro-thermal terms. At high $\beta$ only the N ernst term $i$ n the induction equation affects the solution. At low $\beta$ The Ettingshausen term is larger than thermal conduction at the wall, and the thermal N ernst term is negative. The results are proposed as verification tests for advanced, multi-physics, MHD codes. An example calculation is presented from a 1D MHD simulation code that allows for total pressure changes through the momentum equation. Comparison with the self-similar solution for one case shows that the simulation results approach the self-similar solution.
Property in Transition: Legal Fantasies, Land “Reforms,” and Contracting Peace in Colombia

In Colombia’s attempts to bring its decades-long conflict to a close, the state engaged in a broad endeavor to transition to a new era: the “post-conflict.” In this process, state initiatives to grant land restitution, as well as peace negotiations with FARC guerrillas, billed property as critical to paving the path to peace. This article draws on ethnographic fieldwork in the region of Uraba to explore how and why the relationship between property and peace becomes such a compelling formula for imagining the future, even as projects to reconfigure property for peace keep failing. I argue that legal fantasies, particularly about property and the social contract, become necessary in order to give shape to an aspirational future state in moments of purported transition.
Kantorovich–Rubinstein distance and approximation for non-local Fokker–Planck equations

This work is devoted to studying complex dynamical systems under non-Gaussian fluctuations. We first estimate the Kantorovich–Rubinstein distance for solutions of non-local Fokker–Planck equations associated with stochastic differential equations with non-Gaussian Levy noise. This is then applied to establish weak convergence of the corresponding probability distributions. Furthermore, this leads to smooth approximation for non-local Fokker–Planck equations, as illustrated in an example.
Non-Random Behaviour in Sums of Modular Symbols

We give explicit expressions for the Fourier coefficients of Eisenstein series twisted by Dirichlet characters and modular symbols on $\Gamma_0(N)$ in the case where $N$ is prime and equal to the conductor of the Dirichlet character. We obtain these expressions by computing the spectral decomposition of automorphic functions closely related to these Eisenstein series. As an application, we then evaluate certain sums of modular symbols in a way which parallels past work of Goldfeld, O'Sullivan, Petridis, and Risager. In one case we find less cancellation in this sum than would be predicted by the common phenomenon of ``square root cancellation'', while in another case we find more cancellation.
Gender, job satisfaction and quits: A generational comparison

Job satisfaction has a negative impact on voluntary job quits. If women quit dissatisfying jobs and interrupt their careers more than men, then gender gaps in earnings, labor force participation an...
Periodization and physical therapy: Bridging the gap between training and rehabilitation *

Abstract Background Exercise prescription and training progression for competitive athletes has evolved considerably in recent decades, as strength and conditioning coaches increasingly use periodization models to inform the development and implementation of training programs for their athletes. Similarly, exercise prescription and progression is a fundamental skill for sport physical therapists, and is necessary for balancing the physiological stresses of injury with an athlete's capacity for recovery. Objective This article will provide the sport physical therapist with an overview of periodization models and their application to rehabilitation. Summary In recent decades models for exercise prescription and progression also have evolved in theory and scope, contributing to improved rehabilitation for countless athletes, when compared to care offered to athletes of previous generations. Nonetheless, despite such advances, such models typically fail to fully bridge the gap between such rehabilitation schemes and the corresponding training models that coaches use to help athletes peak for competition. Greater knowledge of periodization models can help sport physical therapists in their evaluation, clinical reasoning skills, exercise progression, and goal setting for the sustained return of athletes to high level competition.
The U.S. home infusion market.

Medicare legislation stimulated the development of home care services but also resulted in fragmentation of service components. In the 1980s, prospective pricing and diagnosis-related groups, and resulting pressures to reduce inpatient length of stay, prompted additional growth of the industry. Even so, in 1995 home care represented only 3% of total national expenditures on health care. The annual growth rate of the home infusion industry dropped from 64% in 1982-86 to 24% in 1986-93. While revenue per patient for home infusion is expected to decrease under managed care, an increasing number of patients will support continued market growth. The home infusion market is highly competitive, with only a few large national providers and many small local providers. In 1996, 29% of acute care hospitals provided or were developing a home care program. Community pharmacists' options in the home infusion area include independent services, partnerships, joint ventures, contracts with hospitals, and franchises. The home infusion market is being integrated into alternative sites, such as ambulatory infusion centers (AICs), as providers attempt to diversify to maintain managed care contracts. AICs provide infusion therapy and nursing to noninstitutionalized, nonhome-bound patients. Untapped sources for future growth of the infusion market include long-term-care facilities. More consistent studies of the home care market are needed. Despite slowed growth in recent years, home care has a strong market in the United States.