Combined Scaling for Open-Vocabulary Image Classification

We present a combined scaling method - named BASIC - that achieves 85.7% top-1 accuracy on the ImageNet ILSVRC-2012 validation set without learning from any labeled ImageNet example. This accuracy surpasses best published similar models - CLIP and ALIGN - by 9.3%. Our BASIC model also shows significant improvements in robustness benchmarks. For instance, on 5 test sets with natural distribution shifts such as ImageNet-{A,R,V2,Sketch} and ObjectNet, our model achieves 84.3% top-1 average accuracy, only a small drop from its original ImageNet accuracy. To achieve these results, we scale up the contrastive learning framework of CLIP and ALIGN in three dimensions: data size, model size, and batch size. Our dataset has 6.6B noisy image-text pairs, which is 4x larger than ALIGN, and 16x larger than CLIP. Our largest model has 3B weights, which is 3.75x larger in parameters and 8x larger in FLOPs than ALIGN and CLIP. Finally, our batch size is 65536 which is 2x more than CLIP and 4x more than ALIGN. We encountered two main challenges with the scaling rules of BASIC. First, the main challenge with implementing the combined scaling rules of BASIC is the limited memory of accelerators, such as GPUs and TPUs. To overcome the memory limit, we propose two simple methods which make use of gradient checkpointing and model parallelism. Second, while increasing the dataset size and the model size has been the defacto method to improve the performance of deep learning models like BASIC, the effect of a large contrastive batch size on such contrastive-trained image-text models is not well-understood. To shed light on the benefits of large contrastive batch sizes, we develop a theoretical framework which shows that larger contrastive batch sizes lead to smaller generalization gaps for image-text models such as BASIC

Standard Penetration Testing in a virtual calibration chamber

The virtual calibration chamber technique, based on the discrete element method, is here applied to study the standard penetration test (SPT). A macro-element approach is used to represent a rod driven with an impact like those applied to perform SPT. The rod is driven into a chamber filled with a scaled discrete analogue of a quartz sand. The contact properties of the discrete analogue are calibrated simulating two low-pressure triaxial tests. The rod is driven changing input energy and controlling initial density and confinement stress. Energy-based blowcount normalization is shown to be effective. Results obtained are in good quantitative agreement with well-accepted experimentally-based relations between blowcount, density and overburden. It is also shown that the tip resistance measured under impact dynamic penetration conditions is close to that under constant velocity conditions, hence supporting recent proposals to relate CPT and SPT results.Peer ReviewedPostprint (author's final draft

To conserve African tropical forests, invest in the protection of its most endangered group of monkeys, red colobus

Forest loss and overhunting are eroding African tropical biodiversity and threatening local human food security, livelihoods, and health. Emblematic of this ecological crisis is Africa's most endangered group of monkeys, the red colobus (genus Piliocolobus). All 17 species, found in forests from Senegal in the west to the Zanzibar archipelago in the east, are threatened with extinction. Red colobus are among the most vulnerable mammals to gun hunting, typically disappearing from heavily hunted forests before most other large-bodied animals. Despite their conservation status, they are rarely a focus of conservation attention and continue to be understudied. However, red colobus can act as critical barometers of forest health and serve as flagships for catalyzing broader African tropical forest conservation efforts. We offer a plan for conservation of red colobus and their habitats and discuss conservation and policy implications.Additional authors: Deo Kujirakwinja, Barney Long, W. Scott McGraw, Russell A. Mittermeier, Thomas T. Struhsake

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

Parenting stress and resilience in parents of children with autism spectrum disorder (ASD) in Southeast Asia: a systematic review

Background: This paper aimed to review the literature on the factors associated with parenting stress and resilience among parents of children with autism spectrum disorder (ASD) in the South East Asia (SEA) region. Methods: An extensive search of articles in multiple online databases (PsycNET, ProQuest, PudMed, EMBASE, CINAHL, Web of Science, and Google Scholar) resulted in 28 papers that met the inclusion criteria (i.e., conducted in the SEA region, specific to ASD only, published in a peer-reviewed journal, full text in English). Studies found were conducted in the following countries: Brunei, n = 1; Indonesia, n = 2; Malaysia, n = 12; Philippines, n = 5; Singapore, n = 5, Thailand, n = 2; and Vietnam, n = 1, but none from Cambodia, East Timor, Laos, and Myanmar were identified. Results: Across the studies, six main factors were found to be associated with parenting stress: social support, severity of autism symptoms, financial difficulty, parents' perception and understanding toward ASD, parents' anxiety and worries about their child's future, and religious beliefs. These six factors could also be categorized as either a source of parenting stress or a coping strategy/resilience mechanism that may attenuate parenting stress. Conclusion: The findings suggest that greater support services in Western countries may underlie the cultural differences observed in the SEA region. Limitations in the current review were identified. The limited number of studies yielded from the search suggests a need for expanded research on ASD and parenting stress, coping, and resilience in the SEA region especially in Cambodia, East Timor, Laos, and Myanmar. The identified stress and resilience factors may serve as sociocultural markers for clinicians, psychologists, and other professionals to consider when supporting parents of children with ASD

Nanostructuring metal-carbon composites for electrochemical biosensors

High performance electrochemical sensors are capable of detecting various biosignals and molecules from biological samples. Particularly, certain analytes with very low concentration within body fluids such as hydrogen peroxide, nitric oxide or heavy metal ions are difficult to be detected. To fabricate electrochemical sensors, novel materials with excellent electrochemical properties are required. Nanostructured carbon-metal composite materials have high performance for electrochemical sensing. While some metal or metal oxide nanoparticles are good at catalysis of analytes, carbon based materials such as graphene and nanotubes are excellent electron-conducting template. Nanocomposites can synergize the properties of various individual nanomaterials, giving rise to materials with enhanced performance and interesting properties. Nanostructuring refers to methods to form small nanoscale particles into high surface area three dimensional networks. Various forms of nanostructuring of these composite materials are explored in this thesis, with carbon based materials as starting template followed by nanostructuring using metal or metal oxides for electrochemical sensors. Namely, electrochemical deposition of gold nanoparticles onto reduced graphene oxide sheets, chemical functionalization between graphene nanosheets and gold nanoparticles, hydrothermal growth of metal oxides onto carbon nanotubes. Through these explorations, a flexible electrode formed by carbon nanotubes is fabricated and gold nanoparticles grown onto the electrode in situ for enzymatic immobilization and detection of glucose. In brief, this research project covers nanostructured metal and carbon composite materials’ synthesis and characterization, utilizing them for electrochemical sensor. By combining these different materials, it is aimed to achieve higher sensitivity and performance, as well as allowing the better understanding on the fundamentals of electron transfer and redox reactions on electrochemical biosensing.DOCTOR OF PHILOSOPHY (SCBE

White light diffuse optical spectroscopy for photodynamic therapy dosimetry

Photodynamic therapy (PDT) is an emerging cancer treatment modality that utilizes light-activated drugs (photosensitizer) and laser light to induce cytotoxicity selectively. It is known that blood oxygenation level and photosensitizer concentration in the tissue play important roles in the PDT treatment efficacy [1,2]. The knowledge of these parameters could also improve or predict the efficacy of the treatment outcome [3]. However, there has been no direct means by which one can measure the parameters during PDT treatment in non-invasive manner. Diffuse Optical Spectroscopy (DOS), which acquires tissue information based on optical absorption, provides a nice solution for this. By applying DOS on the target site of PDT, it is possible to assess the photosensitizer concentration, blood oxygen saturation and blood volume through the measurement of Oxy-Haemoglobin (HbO2) and Deoxy-Haemoglobin (Hb) concentration in situ. This technique has been used in the market with mostly contact based probe and a laser source. In this project, a white light based DOS instrument is built with a switchable (contact or remote) probe. In addition, real time data acquisition software using MATLAB and LabVIEW is also developed. The advantage of having a remote probe is its ability to assess blood oxygenation saturation and photosensitizer concentration during a PDT treatment without obstructing the laser used for PDT. It also removes the need to touch the sensitive surface of the patient’s skin. The preliminary result of instrument testing shows successful measurement of the relative changes of tissue blood oxygenation.Bachelor of Engineering (Chemical and Biomolecular Engineering

Revenue management using seat utilization programme : a Japanese restaurant case study.

Seat optimization is a tool widely used in restaurant revenue management. This study analyses data from a Japanese restaurant, using an optimization technology known as AIMMS to identify the potential for better seat utilization and higher revenue to be obtained. Leveraged on Linear Programming, a model was built to investigate if minimizing the number of empty seats at occupied tables engenders better seat utilization than the present First-Come-First-Serve practice. The results obtained coincide with our original prediction: by minimizing the number of empty seats at occupied tables, seat utilization improves from 1.05% to 15.13%, with an average increase of 5.78%. The augmentation of potential revenue to be generated as a result of more empty seats averages 2.32% of the current revenue generated by the FCFS practice, with the highest percentage change in potential revenue being 7.8% and the lowest at 0.40%. The study also conducts a sensitivity analysis to reflect a more realistic input of the restaurant’s demand. Similar results are obtained: higher seat utilization and higher potential revenue are recognized when the demand increases.BUSINES

Epidemiological Characteristics and Space-Time Analysis of the 2015 Dengue Outbreak in the Metropolitan Region of Tainan City, Taiwan

The metropolitan region of Tainan City in southern Taiwan experienced a dengue outbreak in 2015. This manuscript describes basic epidemiological features of this outbreak and uses spatial and temporal analysis tools to understand the spread of dengue during the outbreak. The analysis found that, independently of gender, dengue incidence rate increased with age, and proportionally affected more males below the age of 40 years but females above the age of 40 years. A spatial scan statistic was applied to detect clusters of disease transmission. The scan statistic found that dengue spread in a north-south diffusion direction, which is across the North, West-Central and South districts of Tainan City. Spatial regression models were used to quantify factors associated with transmission. This analysis indicated that neighborhoods with high proportions of residential area (or low wetland cover) were associated with dengue transmission. However, these association patterns were non-linear. The findings presented here can help Taiwanese public health agencies to understand the fundamental epidemiological characteristics and diffusion patterns of the 2015 dengue outbreak in Tainan City. This type of information is fundamental for policy making to prevent future uncontrolled dengue outbreaks, given that results from this study suggest that control interventions should be emphasized in the North and West-Central districts of Tainan city, in areas with a moderate percentage of residential land cover

Gallium-Doped Tin Oxide Nano-Cuboids for Improved Dye Sensitized Solar Cell

Tin dioxide (SnO2) is a potential candidate to replace conventional titanium dioxide (TiO2) in dye-sensitized solar cells (DSSCs) because of its wider bandgap and higher electron mobility. However, SnO2 suffers from low band edge that causes severe backflow of electrons towards electrolyte (charge recombination). Herein, we demonstrate that gallium (Ga) doping can increase the band edge of SnO2, and we show that DSSCs using a Ga-doped SnO2 nano-cuboids based photoanode offer improved open circuit potential (∼0.74 V), fill factor (∼73.7%), and power conversion efficiency (∼4.05%).ASTAR (Agency for Sci., Tech. and Research, S’pore)Accepted versio