Lanzones Production and Marketing in Laguna, Philippines: Current Practices, Challenges, and Prospects

The province of Laguna in the Philippines has been a major producer of lanzones. The study was conducted to present the profile of the players in the lanzones industry, describe and assess the current performance of the industry, identify problems as well as investment opportunities and recommend possible solutions for the local lanzones industry. Data gathering involved conducting interviews via a survey of 172 lanzones farmers and 30 lanzones traders selected using stratified random sampling and secondary data collection. Results showed that lanzones farmers practice intercropping in view of the crop’s seasonality and better profitability. Challenges include the onslaught of typhoons, fluctuating temperature and pests and diseases. Prospects include the presence of hardy foreign varieties such as ‘duku’ or ‘longkong’ and macrosomatic cloning to boost production. Using new technologies, farmer participation in seminars, intercropping with rambutan and putting up a demo farm for macrosomatic cloning are among the proposed recommendations

Cooperative Business Failures in Batangas Province, Philippines: A Postmortem Analysis

Cooperatives all over the world are said to be imbued with inherent weaknesses and challenges, and therefore, steering these entities towards sustainability is seen as an uphill climb. This paper delves into the reasons why some cooperatives in the Philippines dissolve or stop operating. Specifically, the study aimed to review the literature on factors affecting cooperative business sustainability and failures, to present and analyze two cases of failed multipurpose cooperatives and offer recommendations on operating cooperatives for their continued sustainability. Data was gathered through key informant interviews and secondary sources, and analyzed using the case approach and descriptive analysis. Extant literature primarily pinpointed issues such as poor management, lack of capital, property rights, and portfolio problems as the culprits behind cooperative conversions, failures and restructurings. What made the two multipurpose cooperatives unsustainable were the insufficiency of funds needed to meet Cooperatives Development Authority (CDA) requirements, delinquency of members and their inactive participation in cooperative affairs, mismanagement of resources, absence of a viable marketing system and the lack of a capable financial manager. Cultivating managerial and leadership skills, improving governance, establishing private sector and government linkages and support, encouraging participatory membership, utilizing an effective marketing system, proper resource management and expanding financial knowhow are suggested to achieve cooperative sustainability

Real‐time alerts from AI‐enabled camera traps using the Iridium satellite network: A case‐study in Gabon, Central Africa

Efforts to preserve, protect and restore ecosystems are hindered by long delays between data collection and analysis. Threats to ecosystems can go undetected for years or decades as a result. Real-time data can help solve this issue but significant technical barriers exist. For example, automated camera traps are widely used for ecosystem monitoring but it is challenging to transmit images for real-time analysis where there is no reliable cellular or WiFi connectivity. We modified an off-the-shelf camera trap (Bushnell™) and customised existing open-source hardware to create a ‘smart’ camera trap system. Images captured by the camera trap are instantly labelled by an artificial intelligence model and an ‘alert’ containing the image label and other metadata is then delivered to the end-user within minutes over the Iridium satellite network. We present results from testing in the Netherlands, Europe, and from a pilot test in a closed-canopy forest in Gabon, Central Africa. All reference materials required to build the system are provided in open-source repositories. Results show the system can operate for a minimum of 3 months without intervention when capturing a median of 17.23 images per day. The median time-difference between image capture and receiving an alert was 7.35 min, though some outliers showed delays of 5-days or more when the system was incorrectly positioned and unable to connect to the Iridium network. We anticipate significant developments in this field and hope that the solutions presented here, and the lessons learned, can be used to inform future advances. New artificial intelligence models and the addition of other sensors such as microphones will expand the system's potential for other, real-time use cases including real-time biodiversity monitoring, wild resource management and detecting illegal human activities in protected areas

Fibrosis Progression Rate in Biopsy-Proven Nonalcoholic Fatty Liver Disease Among People With Diabetes Versus People Without Diabetes: A Multicenter Study

Background & aimsThere are limited data regarding fibrosis progression in biopsy-proven nonalcoholic fatty liver disease (NAFLD) in people with type 2 diabetes mellitus (T2DM) compared with people without T2DM. We assessed the time to fibrosis progression in people with T2DM compared with people without T2DM in a large, multicenter, study of people with NAFLD who had paired liver biopsies.MethodsThis study included 447 adult participants (64% were female) with NAFLD who had paired liver biopsies more than 1 year apart. Liver histology was systematically assessed by a central pathology committee blinded to clinical data. The primary outcome was the cumulative incidence of a ≥1-stage increase in fibrosis in participants with T2DM compared with participants without T2DM.ResultsThe mean (SD) age and body mass index (calculated as weight in kilograms divided by the square of the height in meters) were 50.9 (11.5) years and 34.7 (6.3), respectively. The median time between biopsies was 3.3 years (interquartile range, 1.8-6.1 years). Participants with T2DM had a significantly higher cumulative incidence of fibrosis progression at 4 years (24% vs 20%), 8 years (60% vs 50%), and 12 years (93% vs 76%) (P = .005). Using a multivariable Cox proportional hazards model adjusted for multiple confounders, T2DM remained an independent predictor of fibrosis progression (adjusted hazard ratio, 1.69; 95% CI, 1.17-2.43; P = .005). The cumulative incidence of fibrosis regression by ≥1 stage was similar in participants with T2DM compared with participants without T2DM (P = .24).ConclusionsIn this large, multicenter cohort study of well-characterized participants with NAFLD and paired liver biopsies, we found that fibrosis progressed faster in participants with T2DM compared with participants without T2DM. These data have important implications for clinical practice and trial design

Real‐time alerts from AI‐enabled camera traps using the Iridium satellite network: A case‐study in Gabon, Central Africa

Efforts to preserve, protect and restore ecosystems are hindered by long delays between data collection and analysis. Threats to ecosystems can go undetected for years or decades as a result. Real‐time data can help solve this issue but significant technical barriers exist. For example, automated camera traps are widely used for ecosystem monitoring but it is challenging to transmit images for real‐time analysis where there is no reliable cellular or WiFi connectivity.We modified an off‐the‐shelf camera trap (Bushnell™) and customised existing open‐source hardware to create a ‘smart’ camera trap system. Images captured by the camera trap are instantly labelled by an artificial intelligence model and an ‘alert’ containing the image label and other metadata is then delivered to the end‐user within minutes over the Iridium satellite network. We present results from testing in the Netherlands, Europe, and from a pilot test in a closed‐canopy forest in Gabon, Central Africa. All reference materials required to build the system are provided in open‐source repositories.Results show the system can operate for a minimum of 3 months without intervention when capturing a median of 17.23 images per day. The median time‐difference between image capture and receiving an alert was 7.35 min, though some outliers showed delays of 5‐days or more when the system was incorrectly positioned and unable to connect to the Iridium network.We anticipate significant developments in this field and hope that the solutions presented here, and the lessons learned, can be used to inform future advances. New artificial intelligence models and the addition of other sensors such as microphones will expand the system's potential for other, real‐time use cases including real‐time biodiversity monitoring, wild resource management and detecting illegal human activities in protected areas