Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantum singular value transformation and beyond: exponential improvements for quantum matrix arithmetics

An n-qubit quantum circuit performs a unitary operation on an exponentially large, 2n-dimensional, Hilbert space, which is a major source of quantum speed-ups. We develop a new “Quantum singular value transformation” algorithm that can directly harness the advantages of exponential dimensionality by applying polynomial transformations to the singular values of a block of a unitary operator. The transformations are realized by quantum circuits with a very simple structure - typically using only a constant number of ancilla qubits - leading to optimal algorithms with appealing constant factors. We show that our framework allows describing many quantum algorithms on a high level, and enables remarkably concise proofs for many prominent quantum algorithms, ranging from optimal Hamiltonian simulation to various quantum machine learning applications. We also devise a new singular vector transformation algorithm, describe how to exponentially improve the complexity of implementing fractional queries to unitaries with a gapped spectrum, and show how to efficiently implement principal component regression. Finally, we also prove a quantum lower bound on spectral transformations.
Factorized Adversarial Networks for Unsupervised Domain Adaptation

In this paper, we propose Factorized Adversarial Networks (FAN) to solve unsupervised domain adaptation problems for image classification tasks. Our networks map the data distribution into a latent feature space, which is factorized into a domain-specific subspace that contains domain-specific characteristics and a task-specific subspace that retains category information, for both source and target domains, respectively. Unsupervised domain adaptation is achieved by adversarial training to minimize the discrepancy between the distributions of two task-specific subspaces from source and target domains. We demonstrate that the proposed approach outperforms state-of-the-art methods on multiple benchmark datasets used in the literature for unsupervised domain adaptation. Furthermore, we collect two real-world tagging datasets that are much larger than existing benchmark datasets, and get significant improvement upon baselines, proving the practical value of our approach.
On Matching Pursuit and Coordinate Descent

Two popular examples of first-order optimization methods over linear spaces are coordinate descent and matching pursuit algorithms, with their randomized variants. While the former targets the optimization by moving along coordinates, the latter considers a generalized notion of directions. Exploiting the connection between the two algorithms, we present a unified analysis of both, providing affine invariant sublinear $\mathcal{O}(1/t)$ rates on smooth objectives and linear convergence on strongly convex objectives. As a byproduct of our affine invariant analysis of matching pursuit, our rates for steepest coordinate descent are the tightest known. Furthermore, we show the first accelerated convergence rate $\mathcal{O}(1/t^2)$ for matching pursuit and steepest coordinate descent on convex objectives.
On the Long-Term Memory of Deep Recurrent Networks

A key attribute that drives the unprecedented success of modern Recurrent Neural Networks (RNNs) on learning tasks which involve sequential data, is their ability to model intricate long-term temporal dependencies. However, a well established measure of RNNs long-term memory capacity is lacking, and thus formal understanding of the effect of depth on their ability to correlate data throughout time is limited. Specifically, existing depth efficiency results on convolutional networks do not suffice in order to account for the success of deep RNNs on data of varying lengths. In order to address this, we introduce a measure of the network's ability to support information flow across time, referred to as the Start-End separation rank, which reflects the distance of the function realized by the recurrent network from modeling no dependency between the beginning and end of the input sequence. We prove that deep recurrent networks support Start-End separation ranks which are combinatorially higher than those supported by their shallow counterparts. Thus, we establish that depth brings forth an overwhelming advantage in the ability of recurrent networks to model long-term dependencies, and provide an exemplar of quantifying this key attribute which may be readily extended to other RNN architectures of interest, e.g. variants of LSTM networks. We obtain our results by considering a class of recurrent networks referred to as Recurrent Arithmetic Circuits, which merge the hidden state with the input via the Multiplicative Integration operation, and empirically demonstrate the discussed phenomena on common RNNs. Finally, we employ the tool of quantum Tensor Networks to gain additional graphic insight regarding the complexity brought forth by depth in recurrent networks.
Optimization Landscape and Expressivity of Deep CNNs

We analyze the loss landscape and expressiveness of practical deep convolutional neural networks (CNNs) with shared weights and max pooling layers. We show that such CNNs produce linearly independent features at a "wide" layer which has more neurons than the number of training samples. This condition holds e.g. for the VGG network. Furthermore, we provide for such wide CNNs necessary and sufficient conditions for global minima with zero training error. For the case where the wide layer is followed by a fully connected layer we show that almost every critical point of the empirical loss is a global minimum with zero training error. Our analysis suggests that both depth and width are very important in deep learning. While depth brings more representational power and allows the network to learn high level features, width smoothes the optimization landscape of the loss function in the sense that a sufficiently wide network has a well-behaved loss surface with almost no bad local minima.
Prepectoral Breast Reconstruction with Fenestrated Acellular Dermal Matrix: A Novel Design

Summary: Fenestrated acellular dermal matrix (ADM) has improved patient outcomes in both direct-to-implant and 2-stage tissue expander/implant breast reconstruction. This technical alteration utilizes optimal fenestration overlap to enhance the breast reconstruction experience. We present a novel, surgeon-designed shaped fenestrated ADM, placed in the recently repopularized prepectoral pocket for anterior coverage of implants in direct-to-implant and 2-stage breast reconstruction. A retrospective review of 10 patients (18 breasts) who underwent direct-to-implant or 2-stage breast reconstruction utilizing fenestrated shaped ADM in the prepectoral plane at a major academic institution in 2016 was conducted. Sixteen breasts (88.9%) underwent direct-to-implant reconstruction, and 2 breasts (11.1%) received tissue expanders. All reconstructions were performed using FlexHD Pliable ADM with surgeon-designed shape and fenestrations. The average implant size was 544.4 cc (±137.2 cc). The average intraoperative tissue expander fill volume measured 450 cc (90% of tissue expander size). The single expander case utilized 1 office fill (day 21) for full expansion. Major complications requiring reoperation within 90 days postoperatively were observed in 22.2% (4 breasts) of reconstructions. Three breasts (16.7%) due to partial mastectomy flap necrosis, 1 breast (5.5%) explantation due to infection. There was no seroma or capsular contracture. Prepectoral reconstruction with shaped fenestrated ADM is safe with high intraoperative fill volumes and facilitates more direct-to-implant reconstructions. Patients undergo fewer postoperative expansions, experience less time to full expansion, and subjectively report less pain. Patients benefit from improved cosmetic outcomes with better shape and no functional loss or animation deformity.
Maternal body height is a stronger predictor of birth weight than ethnicity: analysis of birth weight percentile charts

Abstract Background Anthropometric parameters such as birth weight (BW) and adult body height vary between ethnic groups. Ethnic-specific percentile charts are currently being used for the assessment of newborns. However, due to globalization and interethnic families, it is unclear which charts should be used. A correlation between a mother’s height and her child’s BW (1 cm accounts for a 17 g increase in BW) has been observed. The study aims to test differences in small for gestational age (SGA) and large for gestational age (LGA) rates, employing BW percentile charts based on maternal height between ethnic groups. Methods This retrospective study of 2.3 million mother/newborn pairs analyzed BW, gestational age, sex, maternal height and ethnicity from the German perinatal survey (1995–2000). These data were stratified for maternal height (≤157, 158–163, 164–169, 170–175, ≥176 cm) and region of origin (Germany, Central and Northern Europe, North America, Mediterranean region, Eastern Europe, Middle East and North Africa, and Asia excluding Middle East). Percentile charts were calculated for each maternal height group. Results The average BW and maternal height differ significantly between ethnic groups. On current percentile charts, newborns of taller mothers (≥176 cm) have a low rate of SGA and a high rate of LGA, whereas newborns of shorter mothers (≤157 cm) have a high rate of SGA and a low rate of LGA. When the BW data are stratified based on the maternal height, mothers of similar height from different ethnic groups show similar average BWs, SGA and LGA rates. Conclusion Maternal body height has a greater influence on BW than maternal ethnicity. The use of BW percentile charts for maternal height should be considered.
Enantioselectivity in the tissue distribution of perhexiline contributes to different effects on hepatic histology and peripheral neural function in rats

Perhexiline, a chiral drug, is a potent antiischemic agent whose clinical utility is limited by hepatic and neural toxicities. It inhibits mitochondrial carnitine palmitoyltransferase‐1, however, excessive inhibition predisposes toward tissue steatosis. This pilot study investigated the distribution of the two enantiomers and their toxicological potential. Dark Agouti rats (n = 4 per group) were administered vehicle or 200 mg/kg daily of racemic, (+)− or (−)‐perhexiline maleate orally for 8 weeks. Plasma biochemical liver function tests and Von Frey assessments of peripheral neural function were performed. Hepatic and neuronal histology, including lipid and glycogen content, was assessed using electron microscopy. Concentrations of the perhexiline enantiomers and metabolites were quantified in plasma, liver and heart. Plasma perhexiline concentrations following administration of racemate, (+)− or (‐)‐enantiomer were within the mid‐upper clinical therapeutic range. There was extensive uptake of both enantiomers into liver and heart, with 2.5‐ to 4.5‐fold greater net uptake of (+)‐ compared to (−)‐perhexiline (P < .05) when administered as pure enantiomers, but not when administered as racemate. There was no biochemical or gross histological evidence of hepatotoxicity. However, livers of animals administered (+)‐perhexiline had higher lipid (P < .01) and lower glycogen (P < .05) content, compared to those administered (−)‐perhexiline. Animals administered racemic perhexiline had reduced peripheral neural function (P < .05) compared to controls or animals administered (−)‐perhexiline. For the same plasma concentrations, differences in tissue distribution may contribute to disparities in the effects of (+)‐ and (−)‐perhexiline on hepatic histology and neural function.
Slow‐Release Formulation of Cowpea Mosaic Virus for In Situ Vaccine Delivery to Treat Ovarian Cancer

The plant viral nanoparticle cowpea mosaic virus (CPMV) is shown to be an effective immunotherapy for ovarian cancer when administered as in situ vaccine weekly, directly into the intraperitoneal (IP) space in mice with disseminated tumors. While the antitumor efficacy is promising, the required frequency of administration may pose challenges for clinical implementation. To overcome this, a slow release formulation is developed. CPMV and polyamidoamine generation 4 dendrimer form aggregates (CPMV‐G4) based on electrostatic interactions and as a function of salt concentration, allowing for tailoring of aggregate size and release of CPMV. The antitumor efficacy of a single administration of CPMV‐G4 is compared to weekly administration of soluble CPMV in a mouse model of peritoneal ovarian cancer and found to be as effective at reducing disease burden as more frequent administrations of soluble CPMV; a single injection of soluble CPMV, does not significantly slow cancer development. The ability of CPMV‐G4 to control tumor growth following a single injection is likely due to the continued presence of CPMV in the IP space leading to prolonged immune stimulation. This enhanced retention of CPMV and its antitumor efficacy demonstrates the potential for viral–dendrimer hybrids to be used for delayed release applications.
Coeliac disease in children with Down syndrome in Ireland

Down syndrome (DS) is one of the most common chromosomal abnormalities with an incidence of 1:444 births.1 Ireland has the highest prevalence of DS in Europe, which may be partially explained by the legislation against termination of pregnancy.1 Individuals with DS are at higher risk of developing coeliac disease (CD) compared with the general population (5%–10% vs 1%). 2 CD can be difficult to diagnose due to the frequency of asymptomatic cases, and it can be particularly difficult to identify clinically in children with DS in whom short stature, abdominal distension and constipation are common clinical features. The European Society …
Inability of Older Adult Patients with Hip Fracture to Maintain Postoperative Weight-Bearing Restrictions

Background: For elderly trauma patients, a basic goal is early mobilization, as immobilization can trigger various complications, such as venous thromboembolism, pneumonia, urinary tract infections, and pressure ulcers. Although partial weight-bearing has been shown to significantly increase mortality compared with unrestricted weight-bearing, it remains a frequent recommendation of aftercare following lower-extremity fracture fixation. Methods: An insole force sensor was used to measure true postoperative weight-bearing by patients ≥75 years of age treated for hip fracture compared with patients 18 to 40 years of age treated for ankle fracture. Both groups were instructed to maintain partial weight-bearing on the affected limb (⩽20 kg) postoperatively. Following standardized physiotherapy training, gait analysis was performed. Results: None of the patients in the elderly test group were able to comply with the weight-bearing restriction as recommended. We found that 69% (11 of 16) of the patients exceeded the specified load by more than twofold, whereas significantly more patients in the younger control group (>75% [14 of 18]) achieved almost the entire weight-bearing restriction (p < 0.001). Only 1 of the elderly patients was able to comply with the predetermined weight-bearing restriction, and only for a short period of time. In comparison, significantly more patients in the control group (89% [16 of 18]; p < 0.001) maintained the partial load for nearly the entire time during gait analysis. Conclusions: Elderly patients seem to be unable to maintain weight-bearing restrictions. As early mobilization of geriatric trauma patients is an important element for a successful rehabilitation, the directive of postoperative partial weight-bearing for these patients should be abandoned. Level of Evidence: Therapeutic Level II. See Instructions for Authors for a complete description of levels of evidence.
Y-Net: A deep Convolutional Neural Network for Polyp Detection

Colorectal polyps are important precursors to colon cancer, the third most common cause of cancer mortality for both men and women. It is a disease where early detection is of crucial importance. Colonoscopy is commonly used for early detection of cancer and precancerous pathology. It is a demanding procedure requiring significant amount of time from specialized physicians and nurses, in addition to a significant miss-rates of polyps by specialists. Automated polyp detection in colonoscopy videos has been demonstrated to be a promising way to handle this problem. {However, polyps detection is a challenging problem due to the availability of limited amount of training data and large appearance variations of polyps. To handle this problem, we propose a novel deep learning method Y-Net that consists of two encoder networks with a decoder network. Our proposed Y-Net method} relies on efficient use of pre-trained and un-trained models with novel sum-skip-concatenation operations. Each of the encoders are trained with encoder specific learning rate along the decoder. Compared with the previous methods employing hand-crafted features or 2-D/3-D convolutional neural network, our approach outperforms state-of-the-art methods for polyp detection with 7.3% F1-score and 13% recall improvement.
Are Older Citizens Using the E-Moi portal in Saudi Arabia, Hail City: A Quantitative Study-‹

ICT has been widely exploited as a powerful tool of development and prosperity. Therefore, Governments are increasingly moving their civil products and services online. However, there are several groups within societies that are missing out on government benefits due to no online access or/and knowledge, including the elderly. This research attempts to understand the factors affecting older adults’ adoption and use of e-government in a vicinity of Saudi Arabia. To achieve this, a quantitative method used an online survey questionnaire resulting in 937 completed responses. The findings offer implications for existing literature on e-Government adoption, for practitioners and policy makers.
Digitalisation and Enterprise Knowledge (net)Working

Social media and emerging mobile technologies have forever changed the landscape of human interaction. Furthermore, they already play a pivotal role also in enterprises as a part of the organisational Knowledge Management System. Almost all large organisations have already implemented at least one Enterprise Social Media tool since they enable collaboration, provide easy access to information, and are available at reasonable costs. The effects of the decoupling of the real and the virtual world (as a result of Social Media use) on the construct “knowledge” and on knowledge management are still not sufficiently investigated. Against this background, the paper presents an exploratory approach of the development of a specific morphological tableau as an instrument for the analysis of employees’ behavior in context of knowledge management related ESM use. Furthermore, the application of the tableau is exemplary illustrated and further research steps are explained.
A Preliminary Study of Work-Focused Cognitive Behavioural Group Therapy for Japanese Workers

Background: In Japan, cognitive behavioural therapy (CBT) has been introduced in the ‘Rework Programme’, but its impact on return to work (RTW) has not been fully clarified. Aims: This pilot study investigated the initial efficacy of a work-focused cognitive behavioural group therapy (WF-CBGT) for Japanese workers on sick leave due to depression. Method: Twenty-three patients on leave due to depression were recruited from a mental health clinic. WF-CBGT including behavioural activation therapy, cognitive therapy, and problem-solving therapy techniques was conducted for eight weekly 150-minute sessions. Participants completed questionnaires on depression and anxiety (Kessler-6), social adaptation (Social Adaptation Self-Evaluation Scale), and difficulty in RTW (Difficulty in Returning to Work Inventory) at pre- and post-intervention time points. Rates of re-instatement after the intervention were examined. Results: One participant dropped out, but 22 participants successfully completed the intervention. All scale scores significantly improved after intervention and, except for difficulty in RTW related to physical fitness, all effect sizes were above the moderate classification. All participants who completed the intervention succeeded in RTW. Conclusions: Results suggested the possibility that WF-CBGT may be a feasible and promising intervention for Japanese workers on leave due to depression regardless of cross-cultural differences, but that additional research examining effectiveness using controlled designs and other samples is needed. Future research should examine the efficacy of this programme more systematically to provide relevant data to aid in the continued development of an evidence-based intervention.
Prevalence and factors associated with metabolic syndrome in an urban population of adults living with HIV in Nairobi, Kenya

Introduction Metabolic syndrome affects 20-25% of the adult population globally. It predisposes to cardiovascular disease and Type 2 diabetes. Studies in other countries suggest a high prevalence of metabolic syndrome among HIV-infected patients but no studies have been reported in Kenya. The objective of this study was to assess the prevalence and factors associated with metabolic syndrome in adult HIV-infected patients in an urban population in Nairobi, Kenya. Methods In a cross-sectional study design, conducted at Riruta Health Centre in 2016, 360 adults infected with HIV were recruited. A structured questionnaire was used to collect data on socio-demography. Blood was collected by finger prick for fasting glucose and venous sampling for lipid profile. Results Using the harmonized Joint Scientific Statement criteria, metabolic syndrome was present in 19.2%. The prevalence was higher among females than males (20.7% vs. 16.0%). Obesity (AOR = 5.37, P < 0.001), lack of formal education (AOR = 5.20, P = 0.002) and family history of hypertension (AOR = 2.06, P = 0.029) were associated with increased odds of metabolic syndrome while physical activity (AOR = 0.28, P = 0.001) was associated with decreased odds. Conclusion Metabolic syndrome is prevalent in this study population. Obesity, lack of formal education, family history of hypertension, and physical inactivity are associated with metabolic syndrome. Screening for risk factors, promotion of healthy lifestyle, and nutrition counselling should be offered routinely in HIV care and treatment clinics.