Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimizing tensor contractions for embedded devices with racetrack memory scratch-pads

Tensor contraction is a fundamental operation in many algorithms with a plethora of applications ranging from quantum chemistry over fluid dynamics and image processing to machine learning. The performance of tensor computations critically depends on the efficient utilization of on-chip memories. In the context of low-power embedded devices, efficient management of the memory space becomes even more crucial, in order to meet energy constraints. This work aims at investigating strategies for performance- and energy-efficient tensor contractions on embedded systems, using racetrack memory (RTM)-based scratch-pad memory (SPM). Compiler optimizations such as the loop access order and data layout transformations paired with architectural optimizations such as prefetching and preshifting are employed to reduce the shifting overhead in RTMs. Experimental results demonstrate that the proposed optimizations improve the SPM performance and energy consumption by 24% and 74% respectively compared to an iso-capacity SRAM.
Harvey Mudd College at SemEval-2019 Task 4: The D.X. Beaumont Hyperpartisan News Detector

We use the 600 hand-labelled articles from SemEval Task 4 to hand-tune a classifier with 3000 features for the Hyperpartisan News Detection task. Our final system uses features based on bag-of-words (BoW), analysis of the article title, language complexity, and simple sentiment analysis in a naive Bayes classifier. We trained our final system on the 600,000 articles labelled by publisher. Our final system has an accuracy of 0.653 on the hand-labeled test set. The most effective features are the Automated Readability Index and the presence of certain words in the title. This suggests that hyperpartisan writing uses a distinct writing style, especially in the title.
CNV_IFTV: An Isolation Forest and Total Variation-Based Detection of CNVs from Short-Read Sequencing Data

Accurate detection of copy number variations (CNVs) from short-read sequencing data is challenging due to the uneven distribution of reads and the unbalanced amplitudes of gains and losses. The direct use of read depths to measure CNVs tends to limit performance. Thus, robust computational approaches equipped with appropriate statistics are required to detect CNV regions and boundaries. This study proposes a new method called CNV_IFTV to address this need. CNV_IFTV assigns an anomaly score to each genome bin through a collection of isolation trees. The trees are trained based on isolation forest algorithm through conducting subsampling from measured read depths. With the anomaly scores, CNV_IFTV uses a total variation model to smooth adjacent bins, leading to a denoised score profile. Finally, a statistical model is established to test the denoised scores for calling CNVs. CNV_IFTV is tested on both simulated and real data in comparison to several peer methods. The results indicate that the proposed method outperforms the peer methods. CNV_IFTV is a reliable tool for detecting CNVs from short-read sequencing data even for low-level coverage and tumor purity. The detection results on tumor samples can aid to evaluate known cancer genes and to predict target drugs for disease diagnosis.
A Many-Objective Evolutionary Algorithm Based on a Two-Round Selection Strategy

Balancing population diversity and convergence is critical for evolutionary algorithms to solve many-objective optimization problems (MaOPs). In this paper, a two-round environmental selection strategy is proposed to pursue good tradeoff between population diversity and convergence for many-objective evolutionary algorithms (MaOEAs). Particularly, in the first round, the solutions with small neighborhood density are picked out to form a candidate pool, where the neighborhood density of a solution is calculated based on a novel adaptive position transformation strategy. In the second round, the best solution in terms of convergence is selected from the candidate pool and inserted into the next generation. The procedure is repeated until a new population is generated. The two-round selection strategy is embedded into an MaOEA framework and the resulting algorithm, namely, 2REA, is compared with eight state-of-the-art MaOEAs on various benchmark MaOPs. The experimental results show that 2REA is very competitive with the compared MaOEAs and the two-round selection strategy works well on balancing population diversity and convergence.
A Hybrid Robotic System for Arm Training of Stroke Survivors: Concept and First Evaluation

Objective: To develop and evaluate a hybrid robotic system for arm recovery after stroke, combining ElectroMyoGraphic (EMG)-triggered functional electrical stimulation (FES) with a passive exoskeleton for upper limb suspension. Methods: The system was used in a structured exercise program resembling activities of daily life. Exercises execution was continuously controlled using angle sensor data and radio-frequency identification technology. The training program consisted of 27 sessions lasting 30 min each. Seven post-acute stroke patients were recruited from two clinical sites. The efficacy of the system was evaluated in terms of action research arm test, motricity index, motor activity log, and box & blocks tests. Furthermore, kinematics-based and EMG-based outcome measures were derived directly from data collected during training sessions. Results: All patients showed an improvement of motor functions at the end of the training program. After training, the exercises were in most cases executed faster, smoother, and with an increased range of motion. Subjects were able to trigger FES, but in some cases, they did not maintain the voluntary effort during task execution. All subjects but one considered the system usable. Conclusion: The preliminary results showed that the system can be used in a clinical environment with positive effects on arm functional recovery. However, only the final results of the currently ongoing clinical trial will unveil the system's full potential. Significance: The presented hybrid robotic system is highly customizable, allows to monitor the daily performance, requires low supervision of the therapist, and might have the potential to enhance arm recovery after stroke.
Evaluation of the diagnostic ability of laminin gene family for pancreatic ductal adenocarcinoma

A poor outcome for pancreatic ductal adenocarcinoma (PDAC) patients is still a challenge worldwide. The aim of our study is to investigate the potential of key laminin subunits for being used both as a diagnostic and prognostic biomarker for PDAC patients. We evaluated the mRNA expression and prognostic value of laminin gene family in PDAC tissues using online public databases. Moreover, the relationship between key laminin subunits in PDAC blood cells and circulating tumor cells (CTCs) and the distinguishing ability of joint serum levels with carbohydrate antigen 19-9 (CA19-9) was analyzed. Two key differentially expressed subunits (LAMA3 and LAMC2) that are associated with prognosis of PDAC patients were found to show a potential for distinguishing between PDAC and non-tumor tissues. LAMA3 and LAMC2 expression were found to be positively related with CTC quantity in PDAC blood (R=0.628, p=0.029; R=0.776, p=0.003, respectively) using IgG chips. Furthermore, serum LAMC2 levels offered significant improvement over using CA19-9 alone for the discrimination of PDAC. Joint serum LAMC2 and CA19-9 levels increased the net benefit proportion in early stage/operational PDAC patients. Using integrated profiling, we identified LAMA3 and LAMC2 as potential therapeutic targets and prognostic markers for PDAC, for which further validation is warranted.
Normal stress difference–driven particle focusing in nanoparticle colloidal dispersion

Micrometer-sized particles, suspended in nanoparticle dispersion, are focused along the channel centerline in Poiseuille microflow. Colloidal dispersion has elastic properties due to Brownian relaxation process. However, experimental evidence for the elastic properties, characterized with normal stress differences, is elusive in shearing colloidal dispersion, particularly at low Péclet numbers (Pe < 1). Here, we report that single micrometer-sized polystyrene (PS) beads, suspended in silica nanoparticle dispersion (8 nm radius; 22%, v/v), laterally migrate and form a tightly focused stream by the normal stress differences, generated in pressure-driven microtube flow at low Pe. The nanoparticle dispersion was expected to behave as a Newtonian fluid because of its ultrashort relaxation time (2 μs), but large shear strain experienced by the PS beads causes the notable non-Newtonian behavior. We demonstrate that the unique rheological properties of the nanoparticle dispersion generate the secondary flow in perpendicular to mainstream in a noncircular conduit, and the elastic properties of blood plasma–constituting protein solutions are elucidated by the colloidal dynamics of protein molecules.
Analysis of the Directivity of Glass-Etalon Fabry–Pérot Ultrasound Sensors

Planar glass-etalon Fabry–Pérot (FP) optical ultrasound sensors offer an alternative to piezoelectric sensors for the measurements of high-intensity focused ultrasound (HIFU) fields and other metrological applications. In this work, a model of the frequency-dependent directional response of the FP sensor was developed using the global matrix method, treating the sensor as a multilayered elastic structure. The model was validated against the experimentally measured directional response of an air-backed cover-slip FP sensor with well-known material properties. In addition, the model was compared with the measurements of an all-hard-dielectric sensor suitable for HIFU measurements. The model was then used to calculate modal dispersion curves for both glass-etalon sensors, allowing the features of the directional response to be linked to specific wave phenomena. The features in the directivity of the air-backed cover-slip sensor are due to guided Lamb waves. Symmetric Lamb modes give rise to regions of high sensitivity, whereas anti-symmetric modes cause regions of low sensitivity. For the all-hard-dielectric sensor, two features correspond to the water-substrate and water-spacer compressional and shear critical angles. A region of high sensitivity close to the shear critical angle is associated with a leaky-Rayleigh wave, which has a frequency-dependent phase speed. At higher frequencies, this feature is counteracted by a region of low sensitivity, which occurs when there is no difference in the vertical displacement of the mirrors forming the FP cavity. The model may be used to improve and optimize the design of FP sensors or could be used to assist with the accurate deconvolution of the directional response from array measurements in metrological and imaging applications.
Predicting Local Inversions Using Rectangle Clustering and Representative Rectangle Prediction

As a specific type of structural variation, inversions are enjoying particular traction as a result of their established role in evolution. Using third-generation sequencing technology to predict inversions is growing in interest, but many such methods focus on improving sensitivity, giving rise to either too many false positives or very long running times. In this paper, we propose a new framework for inversion detection based on a combination of two novel theoretical models: rectangle clustering and representative rectangle prediction. This combination can automatically filter out false positive inversion predictions while retaining correct ones, leading to a method that has both high sensitivity and high positive prediction values (PPV). Further, this new framework can run very fast on available data. Our software can be freely obtained at https://github.com/UTbioinf/RigInv.
Investigating Prebiotic Protocells for a Comprehensive Understanding of the Origins of Life: A Prebiotic Systems Chemistry Perspective

Protocells are supramolecular systems commonly used for numerous applications, such as the formation of self-evolvable systems, in systems chemistry and synthetic biology. Certain types of protocells imitate plausible prebiotic compartments, such as giant vesicles, that are formed with the hydration of thin films of amphiphiles. These constructs can be studied to address the emergence of life from a non-living chemical network. They are useful tools since they offer the possibility to understand the mechanisms underlying any living cellular system: Its formation, its metabolism, its replication and its evolution. Protocells allow the investigation of the synergies occurring in a web of chemical compounds. This cooperation can explain the transition between chemical (inanimate) and biological systems (living) due to the discoveries of emerging properties. The aim of this review is to provide an overview of relevant concept in prebiotic protocell research.
Distributed Adaptive Fuzzy Event-Triggered Containment Control of Nonlinear Strict-Feedback Systems

In this paper, the adaptive fuzzy event-triggered containment control problem is addressed for uncertain nonlinear strict-feedback systems guided by multiple leaders. A novel distributed adaptive fuzzy event-triggered containment control is designed only using the information of the individual follower and its neighbors. Moreover, a distributed event-trigger condition with an adjustable threshold is developed simultaneously. The designed containment control law is updated in an aperiodic manner, only when event-triggered errors exceed tolerable thresholds. It is proved that the uniformly ultimately bounded containment control can be achieved, and there is no Zeno behavior exhibited by applying the proposed control scheme. Simulation studies are outlined to illustrate the effectiveness of the theoretical results and the advantages of the event-triggered containment control proposed in this paper.
Differentiation of Underlying Pathologies of Macular Edema Using Spectral Domain Optical Coherence Tomography (SD-OCT)

ABSTRACT Purpose: To describe the morphological characteristics of macular edema (ME) of different origins using spectral domain optical coherence tomography (SD-OCT). Methods: This article summarizes and highlights key morphologic findings, based on published articles, describing the characteristic presentations of ME of different origins using SD-OCT. The following pathologies were included: uveitic macular edema, pseudophakic cystoid macular edema (PCME), diabetic macular edema (DME), macular edema secondary to central or branch retinal vein occlusion (CRVO/BRVO), microcystic macular edema (MME), ME associated with epiretinal membrane (ERM), and retinitis pigmentosa (RP). Conclusions: Macular edema of different origins show characteristic patterns that are often indicative of the underlying cause and pathology. Thus, trained algorithms may in the future be able to automatically differentiate underlying causes and support clinical diagnosis. Knowledge of different appearances support the clinical diagnosis and can lead to improved and more targeted treatment of ME.
Emerging therapies in Huntington’s disease

ABSTRACT Introduction: Huntington’s disease (HD) is an inherited neurodegenerative condition for which there are no disease-modifying treatments. The availability of early genetic diagnosis makes HD an ideal candidate for early intervention. Growing understanding of pathogenesis has led to the identification of new therapeutic targets for which some compounds are now in clinical trials. Areas covered: A detailed review of medical databases and clinical trial registries was performed. Recent clinical trials aimed to establish disease-modification were included. Focus was assigned to RNA and DNA-based therapies aimed at lowering mutant huntingtin (mHTT) including antisense oligonucleotides (ASOs), RNA interference (RNAi), zinc finger proteins (ZFPs) and the CRISPR-Cas9 system. Modulation of mHTT and immunotherapies is also covered. Expert opinion: Targeting HD pathogenesis at its most proximal level is under intense investigation. ASOs are the only HTT-lowering strategy in clinical trials of manifest HD. Safety and efficacy of an allele specific vs. allele non-specific approach has yet to be established. Success will extend to premanifest carriers for which development of clinical and imaging biomarkers will be necessary. Scientific and technological advancement will bolster new methods of treatment delivery. Cumulative experience, collaborative research, and platforms such as ENROLL-HD will facilitate efficient and effective clinical trials.
Dietary Glycemic Index and Glycemic Load and the Risk of Prostate Cancer: An Updated Systematic Review and Dose–Response Meta-Analysis

Abstract A meta-analysis in 2015 revealed no significant association between glycemic index (GI), glycemic load (GL), and prostate cancer. Moreover, until now, no study has examined the dose–response association of GI, GL, and prostate cancer yet. The online databases were searched by two independent researchers for relevant publications up to Jan. 2019, using relevant keywords. Nine studies including five prospective and four case–control studies were included in the current systematic review and meta-analysis. These studies have included 290,911 individuals. We found a significant positive dose–response association between dietary GI and prostate cancer (Pnonlinearity = 0.03). Comparing individuals in the highest category of GI with those in the lowest category, no significant association was found between GI and prostate cancer (combined effect size: 1.08, 95% CI: 0.97–1.19, P = 0.17). Furthermore, no significant association was seen between dietary GL and prostate cancer in both dose–response analysis and when comparing the highest versus lowest categories of GL (combined effect size: 1.03, 95% CI: 0.91–1.16, P = 0.65). In conclusion, we found a significant positive dose–response association between dietary GI and prostate cancer. However, significant association was not seen for dietary GL.
LFP-Based Gravure Printed Cathodes for Lithium-Ion Printed Batteries

Printed batteries have undergone increased investigation in recent years because of the growing daily use of small electronic devices. With this in mind, industrial gravure printing has emerged as a suitable production technology due to its high speed and quality, and its capability to produce any shape of image. The technique is one of the most appealing for the production of functional layers for many different purposes, but it has not been highly investigated. In this study, we propose a LiFePO4 (LFP)-based gravure printed cathode for lithium-ion rechargeable printed batteries and investigate the possibility of employing this printing technique in battery manufacture.
Does conventional freezing affect sperm DNA fragmentation?

Objective Sperm cryopreservation has been widely used in assisted reproductive technology, as it offers great potential for the treatment of some types of male infertility. However, cryopreservation may result in changes in membrane lipid composition and acrosome status, as well as reductions in sperm motility and viability. This study aimed to evaluate sperm DNA fragmentation damage caused by conventional freezing using the sperm chromatin dispersion test. Methods In total, 120 fresh human semen samples were frozen by conventional methods, using SpermFreeze Solution as a cryoprotectant. Routine semen analysis and a Halosperm test (using the Halosperm kit) were performed on each sample before freezing and after thawing. Semen parameters and sperm DNA fragmentation were compared between these groups. Results There was a significant decrease in sperm progressive motility, viability, and normal morphology after conventional freezing (32.78%, 79.58%, and 3.87% vs. 16%, 55.99%, and 2.55%, respectively). The sperm head, midpiece, and tail defect rate increased slightly after freezing. Furthermore, the DNA fragmentation index (DFI) was significantly higher after thawing than before freezing (19.21% prior to freezing vs. 22.23% after thawing). Significant increases in the DFI after cryopreservation were observed in samples with both normal and abnormal motility and morphology, as well as in those with normal viability. Conclusion Conventional freezing seems to damage some sperm parameters, in particular causing a reduction in sperm DNA integrity.
Rapidly and highly efficient degradation of tetracycline hydrochloride in wastewater by 3D IO-TiO2-CdS nanocomposite under visible light

ABSTRACT Tetracycline hydrochloride as an environmental pollutant is biologically toxic and highly difficult to degrade. To solve this problem, an efficient catalyst IO-TiO2-CdS composite with honeycomb-like three-dimensional (3D) inverse opal TiO2 (IO-TiO2) and cadmium sulphide (CdS) was synthesized and applied in the degradation of tetracycline hydrochloride in this paper. More than 99% of the tetracycline hydrochloride (30 mg/L) can be degraded by IO-TiO2-CdS (30 mg) within 20 min under visible light irradiation. Surprisingly, the naphthol rings can be opened and degraded to alkane with a minimum molecular weight of 60, which is the smallest fragment among all publications. The three-dimensional ordered macroporous (3DOM) structure of IO-TiO2 improves the utilization of light via the slow photon effect. Meanwhile, the addition of CdS enhances the degradation efficiency of tetracycline by broadening the range of absorption spectrum and improving the separation of charge carrier on the catalyst. In addition to the degradation of tetracycline hydrochloride, IO-TiO2-CdS also shows a good degradation efficiency of Rhodamine B (RhB). This work provides a promising approach to construct visible light response photocatalysts with non-noble metal for efficient degradation of wastewater pollutants. GRAPHICAL ABSTRACT
Anaerobic-aerobic sequential treatment: Temperature optimization and cost implications

ABSTRACT Traditionally, aeration units, used as a polishing stage after anaerobic digestion (AD) of wastes, are operated at ambient temperature. Yet, when effluent quality is the main design criterion, raising the temperature of the aeration stage can be justified by improved removal efficiencies. In this study, an anaerobic-aerobic sequential system (AASS) was operated to co-digest raw wastewater and food waste. The aerobic compartment was tested under psychrophilic and mesophilic temperatures. At the design loading rate of 2 gVS L−1 d−1, the anaerobic digester achieved removal efficiencies of 85 ± 2% of volatile solids (VS), 84 ± 3% of total chemical oxygen demand (CODT) and a biogas yield of 1,035 ± 30 mL gVSfed−1 (50% methane). The aerobic reactor achieved additional removal of 8% CODT and 7 % VS. By raising the temperature of the aerobic reactor to the mesophilic range, COD and solids concentrations of the effluent dropped to approximately half their values. This was accompanied by an increase in nitrification (from 68% to 91%) and denitrification (from 10% to 16%). The energy analysis showed that total energy consumption slightly increases (from 0.45 to 0.49 kWh kgCODfed−1) by raising the temperature of the aerobic reactor to mesophilic range. A preliminary evaluation of the sludge disposal cost, revealed a saving increase of 5–6% under mesophilic operation with respect to psychrophilic conditions. Implications: In order to cope with the globally increasing constraints on the disposal of urban wastes, efficient post-processing of effluents becomes a crucial requirement for the anaerobic digestion industry. In this context, the submitted manuscript shows that the quality of the effluent, of an anaerobic digester, treating food waste with raw wastewater, can be substantially improved by optimizing the aerobic polishing stage. Raising the temperature of the aerobic reactor to the mesophilic range resulted in a drop of solids and COD concentrations to approximately half their values. Equally important, the implications on operational costs were found to be favorable, compared to traditional psychrophilic aerobic post-treatment, when taking into consideration indirect sludge treatment costs and energy selling revenues.