MENGUKUR MARKET PERFORMANCE MELALUI PROCESS INNOVATION, MARKETING INNOVATION, DAN PRODUCT INNOVATION PADA USAHA KECIL MENENGAH (UKM) SEKTOR MAKANAN DAN MINUMAN DI KOTA PADANG

Penelitian ini bertujuan untuk menguji dan menganalisa process innovation dan product innovation, kemudian semenarik apa marketing innovation akan menambah daya tarik konsumen untuk meningkatkan SME’s Market performance, dengan menggunakan teknik non-probability sampling total 104 sampel. Kemudian data dianalisis menggunakan bantuan, Smart PLS Software version 3. Hasil penelitian menemukan bahwa marketing innovation berpengaruh positif dan signifikan terhadap market performance, marketing innovation berpengaruh positif dan signifikan terhadap product innovation, process innovation berpengaruh positif dan signifikan terhadap product innovation, product innovation berpengaruh positif dan signifikan terhadap market peformance, serta product innovation yang memberikan efek mediasi parsial pada hubungan marketing innovation dan market performance

An integrated assessment model for food security under climate change for South Asia

The present study develops an integrated assessment model (IAM) for food security under climate change for South Asia. For IAM, initially, an econometric model is estimated that identifies the impact of climate change on crop yields, using the historical relationships between temperature, precipitation, and the production of cereals. Subsequently, future projections have been collected for temperature and precipitation from climate models of the Coupled Model Inter-comparison Project Phase 5 (CMIP5), and the previous econometric model is applied to obtain the implied future cereal yields changes. Then, the yield variations are fed into a multiregional Global Trade Analysis Project (GTAP) model, calibrated to the GTAP 9 database, taking the form of decreases in factor-augmenting productivity of the grains sector. Further, the present study evaluates the effects of climate change on an individual South Asian country. The results indicate that change in climate decreases food production, increases food prices, decreases food consumption, and thus affects the welfare. Trade and fiscal policy responses are investigated to combat the problem of food security. It is revealed that these two policies fail to compensate climate change damage in all the selected South Asian countries

Do Farmers Adapt to Climate Change? A Macro Perspective

Greenhouse gas emissions cause climate change, and agriculture is the most vulnerable sector. Farmers do have some capability to adapt to changing weather and climate, but this capability is contingent on many factors, including geographical and socioeconomic conditions. Assessing the actual adaptation potential in the agricultural sector is therefore an empirical issue, to which this paper contributes by presenting a study examining the impacts of climate change on cereal yields in 55 developing and developed countries, using data from 1991 to 2015. The results indicate that cereal yields are affected in all regions by changes in temperature and precipitation, with significant differences in certain macro-regions in the world. In Southern Asia and Central Africa, farmers fail to adapt to climate change. The findings suggest that the world should focus more on enhancing adaptive capacity to moderate potential damage and on coping with the consequences of climate change

NeuroAssist: Open-Source Automatic Event Detection in Scalp EEG

Localisation of clinically relevant events within Electroencephalogram (EEG) recordings can be useful for explaining the decisions made by automated EEG screening and decision support systems. The majority of existing deep learning based approaches that have been proposed in recent literature only classify EEG records as normal or pathological without providing any justification for their decisions and thus are not very transparent. In clinical practice it is often observed that a significant proportion of EEG recordings does not contain any abnormal (or pathological) events; even in cases classified as pathological. If deployed in practice such a setup would not be very useful since it would require neurologists to invest additional time, manually searching for events within an EEG recording before accepting or rejecting the decision proposed by the automated system. This work presents open-source software that can automatically localise and classify abnormalities both across time and EEG channels. Our work can thus be used to reveal the reasons behind an EEG recording being classified as normal or pathological/abnormal. Training an automated event localisation system requires a dataset containing fine-grained labels pointing out precise locations of events. To facilitate further development we are also releasing the dataset and annotations used in this work for use by the research community. This dataset contains 1,075 EEG recordings with precise temporal and channel locations of two broad categories of abnormal events: (i) Epileptiform discharges and (ii) Non-epileptiform abnormalities. Our localisation system is based on features derived from wavelet transforms. For event classification we investigated the performance of both classic machine learning algorithms (support vector machines, decision trees, random forest classifier) and deep convolutional neural networks (VGG16, GoogLeNet and EfficientNet). Our results indicate that deep convolutional neural networks outperform classic machine learning algorithms in terms of average values of precision, recall, F1-score and accuracy

Inhibition of G-protein signalling in cardiac dysfunction of intellectual developmental disorder with cardiac arrhythmia (IDDCA) syndrome.

BACKGROUND: Pathogenic variants of GNB5 encoding the β5 subunit of the guanine nucleotide-binding protein cause IDDCA syndrome, an autosomal recessive neurodevelopmental disorder associated with cognitive disability and cardiac arrhythmia, particularly severe bradycardia. METHODS: We used echocardiography and telemetric ECG recordings to investigate consequences of Gnb5 loss in mouse. RESULTS: We delineated a key role of Gnb5 in heart sinus conduction and showed that Gnb5-inhibitory signalling is essential for parasympathetic control of heart rate (HR) and maintenance of the sympathovagal balance. Gnb5-/- mice were smaller and had a smaller heart than Gnb5+/+ and Gnb5+/- , but exhibited better cardiac function. Lower autonomic nervous system modulation through diminished parasympathetic control and greater sympathetic regulation resulted in a higher baseline HR in Gnb5-/- mice. In contrast, Gnb5-/- mice exhibited profound bradycardia on treatment with carbachol, while sympathetic modulation of the cardiac stimulation was not altered. Concordantly, transcriptome study pinpointed altered expression of genes involved in cardiac muscle contractility in atria and ventricles of knocked-out mice. Homozygous Gnb5 loss resulted in significantly higher frequencies of sinus arrhythmias. Moreover, we described 13 affected individuals, increasing the IDDCA cohort to 44 patients. CONCLUSIONS: Our data demonstrate that loss of negative regulation of the inhibitory G-protein signalling causes HR perturbations in Gnb5-/- mice, an effect mainly driven by impaired parasympathetic activity. We anticipate that unravelling the mechanism of Gnb5 signalling in the autonomic control of the heart will pave the way for future drug screening

Surgical site infection after gastrointestinal surgery in high-income, middle-income, and low-income countries: a prospective, international, multicentre cohort study

Background: Surgical site infection (SSI) is one of the most common infections associated with health care, but its importance as a global health priority is not fully understood. We quantified the burden of SSI after gastrointestinal surgery in countries in all parts of the world. Methods: This international, prospective, multicentre cohort study included consecutive patients undergoing elective or emergency gastrointestinal resection within 2-week time periods at any health-care facility in any country. Countries with participating centres were stratified into high-income, middle-income, and low-income groups according to the UN's Human Development Index (HDI). Data variables from the GlobalSurg 1 study and other studies that have been found to affect the likelihood of SSI were entered into risk adjustment models. The primary outcome measure was the 30-day SSI incidence (defined by US Centers for Disease Control and Prevention criteria for superficial and deep incisional SSI). Relationships with explanatory variables were examined using Bayesian multilevel logistic regression models. This trial is registered with ClinicalTrials.gov, number NCT02662231. Findings: Between Jan 4, 2016, and July 31, 2016, 13 265 records were submitted for analysis. 12 539 patients from 343 hospitals in 66 countries were included. 7339 (58·5%) patient were from high-HDI countries (193 hospitals in 30 countries), 3918 (31·2%) patients were from middle-HDI countries (82 hospitals in 18 countries), and 1282 (10·2%) patients were from low-HDI countries (68 hospitals in 18 countries). In total, 1538 (12·3%) patients had SSI within 30 days of surgery. The incidence of SSI varied between countries with high (691 [9·4%] of 7339 patients), middle (549 [14·0%] of 3918 patients), and low (298 [23·2%] of 1282) HDI (p < 0·001). The highest SSI incidence in each HDI group was after dirty surgery (102 [17·8%] of 574 patients in high-HDI countries; 74 [31·4%] of 236 patients in middle-HDI countries; 72 [39·8%] of 181 patients in low-HDI countries). Following risk factor adjustment, patients in low-HDI countries were at greatest risk of SSI (adjusted odds ratio 1·60, 95% credible interval 1·05–2·37; p=0·030). 132 (21·6%) of 610 patients with an SSI and a microbiology culture result had an infection that was resistant to the prophylactic antibiotic used. Resistant infections were detected in 49 (16·6%) of 295 patients in high-HDI countries, in 37 (19·8%) of 187 patients in middle-HDI countries, and in 46 (35·9%) of 128 patients in low-HDI countries (p < 0·001). Interpretation: Countries with a low HDI carry a disproportionately greater burden of SSI than countries with a middle or high HDI and might have higher rates of antibiotic resistance. In view of WHO recommendations on SSI prevention that highlight the absence of high-quality interventional research, urgent, pragmatic, randomised trials based in LMICs are needed to assess measures aiming to reduce this preventable complication